Dataset Viewer
Auto-converted to Parquet Duplicate
id
large_stringlengths
9
16
submitter
large_stringlengths
1
64
authors
large_stringlengths
4
60.7k
title
large_stringlengths
1
381
comments
large_stringlengths
1
827
journal-ref
large_stringlengths
1
557
doi
large_stringlengths
8
153
report-no
large_stringlengths
2
509
categories
large_stringlengths
5
125
license
large_stringclasses
9 values
abstract
large_stringlengths
6
5.67k
update_date
timestamp[ms]date
2007-05-23 00:00:00
2026-02-20 00:00:00
classification_label
stringclasses
2 values
is_new_dataset
bool
2 classes
confidence_score
float64
0.5
0.72
classification_date
stringdate
2026-03-01 00:45:07
2026-03-01 00:45:07
model_version
stringclasses
1 value
2505.24687
Shengyuan Liu
Shengyuan Liu, Wenting Chen, Boyun Zheng, Wentao Pan, Xiang Li, Yixuan Yuan
TumorGen: Boundary-Aware Tumor-Mask Synthesis with Rectified Flow Matching
10 pages, 4 figures
null
null
null
eess.IV cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tumor data synthesis offers a promising solution to the shortage of annotated medical datasets. However, current approaches either limit tumor diversity by using predefined masks or employ computationally expensive two-stage processes with multiple denoising steps, causing computational inefficiency. Additionally, thes...
2025-06-02T00:00:00
no_new_dataset
false
0.711725
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24689
Sander Land
Sander Land, Catherine Arnett
BPE Stays on SCRIPT: Structured Encoding for Robust Multilingual Pretokenization
9 pages, 2 figures. For associated code, see https://github.com/sanderland/script_bpe
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Byte Pair Encoding (BPE) tokenizers, widely used in Large Language Models, face challenges in multilingual settings, including penalization of non-Western scripts and the creation of tokens with partial UTF-8 sequences. Pretokenization, often reliant on complex regular expressions, can also introduce fragility and unex...
2025-06-02T00:00:00
no_new_dataset
false
0.709918
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24690
Simone Alberto Peirone
Simone Alberto Peirone and Francesca Pistilli and Antonio Alliegro and Tatiana Tommasi and Giuseppe Averta
Learning reusable concepts across different egocentric video understanding tasks
Extended abstract derived from arXiv:2502.02487. Presented at the Second Joint Egocentric Vision (EgoVis) Workshop (CVPR 2025)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Our comprehension of video streams depicting human activities is naturally multifaceted: in just a few moments, we can grasp what is happening, identify the relevance and interactions of objects in the scene, and forecast what will happen soon, everything all at once. To endow autonomous systems with such holistic perc...
2025-06-02T00:00:00
no_new_dataset
false
0.706948
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24692
Derek Everett
Derek Everett, Fred Lu, Edward Raff, Fernando Camacho, James Holt
Quick-Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms
KDD 2025, Research Track
null
10.1145/3711896.3737097
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Canonical algorithms for multi-armed bandits typically assume a stationary reward environment where the size of the action space (number of arms) is small. More recently developed methods typically relax only one of these assumptions: existing non-stationary bandit policies are designed for a small number of arms, whil...
2025-06-02T00:00:00
no_new_dataset
false
0.712301
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24693
Julio Silva-Rodr\'iguez
Julio Silva-Rodr\'iguez and Ismail Ben Ayed and Jose Dolz
Conformal Prediction for Zero-Shot Models
CVPR 2025. Code: https://github.com/jusiro/CLIP-Conformal
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Vision-language models pre-trained at large scale have shown unprecedented adaptability and generalization to downstream tasks. Although its discriminative potential has been widely explored, its reliability and uncertainty are still overlooked. In this work, we investigate the capabilities of CLIP models under the spl...
2025-06-02T00:00:00
no_new_dataset
false
0.711678
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24697
Aaron Conrardy
Aaron Conrardy, Alfredo Capozucca, Jordi Cabot
Towards a unified user modeling language for engineering human centered AI systems
Accepted at the Third Workshop on Engineering Interactive Systems Embedding AI Technologies (EISEAIT workshop at EICS 2025)
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
In today's digital society, personalization has become a crucial aspect of software applications, significantly impacting user experience and engagement. A new wave of intelligent user interfaces, such as AI-based conversational agents, has the potential to enable such personalization beyond what other types of interfa...
2025-06-02T00:00:00
no_new_dataset
false
0.709283
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24701
Tejul Pandit
Tejul Pandit, Meet Raval, and Dhvani Upadhyay
Multi-Domain ABSA Conversation Dataset Generation via LLMs for Real-World Evaluation and Model Comparison
11 pages, 3 figures, 5 tables, 6th International Conference on Natural Language Computing and AI (NLCAI 2025), ISBN : 978-1-923107-59-5, Computer Science & Information Technology (CS & IT), ISSN : 2231 - 5403, Volume 15, Number 10, May 2025
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Aspect-Based Sentiment Analysis (ABSA) offers granular insights into opinions but often suffers from the scarcity of diverse, labeled datasets that reflect real-world conversational nuances. This paper presents an approach for generating synthetic ABSA data using Large Language Models (LLMs) to address this gap. We det...
2025-06-02T00:00:00
no_new_dataset
false
0.704983
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24703
Dennis Jacob
Dennis Jacob, Chong Xiang, Prateek Mittal
PatchDEMUX: A Certifiably Robust Framework for Multi-label Classifiers Against Adversarial Patches
CVPR 2025
null
null
null
cs.CR cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning techniques have enabled vast improvements in computer vision technologies. Nevertheless, these models are vulnerable to adversarial patch attacks which catastrophically impair performance. The physically realizable nature of these attacks calls for certifiable defenses, which feature provable guarantees o...
2025-06-02T00:00:00
no_new_dataset
false
0.712214
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24704
Hideaki Kim
Hideaki Kim, Tomoharu Iwata, Akinori Fujino
K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
Accepted to ICML 2025
null
null
null
stat.ML cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Kernel method-based intensity estimators, formulated within reproducing kernel Hilbert spaces (RKHSs), and classical kernel intensity estimators (KIEs) have been among the most easy-to-implement and feasible methods for estimating the intensity functions of inhomogeneous Poisson processes. While both approaches share t...
2025-06-02T00:00:00
no_new_dataset
false
0.710724
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24709
Soichiro Nishimori
Soichiro Nishimori, Yu-Jie Zhang, Thanawat Lodkaew, and Masashi Sugiyama
On Symmetric Losses for Robust Policy Optimization with Noisy Preferences
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Optimizing policies based on human preferences is key to aligning language models with human intent. This work focuses on reward modeling, a core component in reinforcement learning from human feedback (RLHF), and offline preference optimization, such as direct preference optimization. Conventional approaches typically...
2025-06-02T00:00:00
no_new_dataset
false
0.710004
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24710
Wei Chen
Wei Chen, Jiahao Zhang, Haipeng Zhu, Boyan Xu, Zhifeng Hao, Keli Zhang, Junjian Ye, Ruichu Cai
Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting
Accepted by IJCAI 2025
null
null
null
cs.LG cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) have shown great potential in decision-making due to the vast amount of knowledge stored within the models. However, these pre-trained models are prone to lack reasoning abilities and are difficult to adapt to new environments, further hindering their application to complex real-world tasks...
2025-06-02T00:00:00
no_new_dataset
false
0.71257
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24712
Guido Ivetta
Guido Ivetta (1 and 2), Marcos J. Gomez (1 and 2), Sof\'ia Martinelli (1), Pietro Palombini (1), M. Emilia Echeveste (1 and 2), Nair Carolina Mazzeo (2), Beatriz Busaniche (2), Luciana Benotti (1 and 2) ((1) Universidad Nacional de C\'ordoba, Argentina, (2) Fundaci\'on V\'ia Libre)
HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America
null
null
null
null
cs.CL cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
Most resources for evaluating social biases in Large Language Models are developed without co-design from the communities affected by these biases, and rarely involve participatory approaches. We introduce HESEIA, a dataset of 46,499 sentences created in a professional development course. The course involved 370 high-s...
2025-06-02T00:00:00
new_dataset
true
0.709577
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24713
Badr M. Abdullah
Badr M. Abdullah, Matthew Baas, Bernd M\"obius, Dietrich Klakow
Voice Conversion Improves Cross-Domain Robustness for Spoken Arabic Dialect Identification
Accepted in Interspeech 2025
null
null
null
cs.CL cs.SD eess.AS
http://creativecommons.org/licenses/by-nc-nd/4.0/
Arabic dialect identification (ADI) systems are essential for large-scale data collection pipelines that enable the development of inclusive speech technologies for Arabic language varieties. However, the reliability of current ADI systems is limited by poor generalization to out-of-domain speech. In this paper, we pre...
2025-06-02T00:00:00
new_dataset
true
0.711175
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24714
Junyu Luo
Junyu Luo, Zhizhuo Kou, Liming Yang, Xiao Luo, Jinsheng Huang, Zhiping Xiao, Jingshu Peng, Chengzhong Liu, Jiaming Ji, Xuanzhe Liu, Sirui Han, Ming Zhang, Yike Guo
FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation
ACL 2025 Main Conference
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Multimodal Large Language Models (MLLMs) have experienced rapid development in recent years. However, in the financial domain, there is a notable lack of effective and specialized multimodal evaluation datasets. To advance the development of MLLMs in the finance domain, we introduce FinMME, encompassing more than 11,00...
2025-06-02T00:00:00
new_dataset
true
0.715607
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24715
Prabhu Teja Sivaprasad
Fabio Fehr, Prabhu Teja Sivaprasad, Luca Franceschi, Giovanni Zappella
CoRet: Improved Retriever for Code Editing
ACL 2025
null
null
null
cs.LG cs.AI cs.CL
http://creativecommons.org/licenses/by-nc-nd/4.0/
In this paper, we introduce CoRet, a dense retrieval model designed for code-editing tasks that integrates code semantics, repository structure, and call graph dependencies. The model focuses on retrieving relevant portions of a code repository based on natural language queries such as requests to implement new feature...
2025-06-02T00:00:00
no_new_dataset
false
0.712118
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24716
Christopher Buss
Christopher Buss, Mahdis Safari, Arash Termehchy, Stefan Lee, David Maier
Towards Scalable Schema Mapping using Large Language Models
null
null
null
null
cs.DB cs.AI
http://creativecommons.org/licenses/by/4.0/
The growing need to integrate information from a large number of diverse sources poses significant scalability challenges for data integration systems. These systems often rely on manually written schema mappings, which are complex, source-specific, and costly to maintain as sources evolve. While recent advances sugges...
2025-06-02T00:00:00
no_new_dataset
false
0.713058
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24717
Benjamin Holzschuh
Benjamin Holzschuh, Qiang Liu, Georg Kohl and Nils Thuerey
PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations
ICML 2025. Code available at https://github.com/tum-pbs/pde-transformer
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce PDE-Transformer, an improved transformer-based architecture for surrogate modeling of physics simulations on regular grids. We combine recent architectural improvements of diffusion transformers with adjustments specific for large-scale simulations to yield a more scalable and versatile general-purpose tra...
2025-06-02T00:00:00
no_new_dataset
false
0.710279
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24721
Nick Rossenbach
Nick Rossenbach, Benedikt Hilmes, Leon Brackmann, Moritz Gunz, Ralf Schl\"uter
Running Conventional Automatic Speech Recognition on Memristor Hardware: A Simulated Approach
Accepted for the Blue Sky track at Interspeech 2025
null
null
null
cs.LG cs.AR cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Memristor-based hardware offers new possibilities for energy-efficient machine learning (ML) by providing analog in-memory matrix multiplication. Current hardware prototypes cannot fit large neural networks, and related literature covers only small ML models for tasks like MNIST or single word recognition. Simulation c...
2025-06-02T00:00:00
no_new_dataset
false
0.709616
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24724
Zhipeng Wang
Xihan Xiong, Zhipeng Wang, Qin Wang, Endong Liu, Pascal Berrang, William Knottenbelt
Talking Transactions: Decentralized Communication through Ethereum Input Data Messages (IDMs)
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Can you imagine, blockchain transactions can talk! In this paper, we study how they talk and what they talk about. We focus on the input data field of Ethereum transactions, which is designed to allow external callers to interact with smart contracts. In practice, this field also enables users to embed natural language...
2025-06-02T00:00:00
no_new_dataset
false
0.707087
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24725
Ali W. Elshaari
Jun Gao, Jin Chang, Bruno Lopez Rodriguez, Iman Esmaeil Zadeh, Val Zwiller, Ali W. Elshaari
From Pixels to Camera: Scaling Superconducting Nanowire Single-Photon Detectors for Imaging at the Quantum-Limit
null
null
null
null
quant-ph cond-mat.supr-con physics.app-ph physics.optics
http://creativecommons.org/licenses/by/4.0/
Superconducting nanowire single-photon detectors (SNSPDs) have emerged as essential devices that push the boundaries of photon detection with unprecedented sensitivity, ultrahigh timing precision, and broad spectral response. Recent advancements in materials engineering, superconducting electronics integration, and cry...
2025-06-02T00:00:00
no_new_dataset
false
0.71324
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24726
Melisa Russak
Shelly Bensal, Umar Jamil, Christopher Bryant, Melisa Russak, Kiran Kamble, Dmytro Mozolevskyi, Muayad Ali, Waseem AlShikh
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
We explore a method for improving the performance of large language models through self-reflection and reinforcement learning. By incentivizing the model to generate better self-reflections when it answers incorrectly, we demonstrate that a model's ability to solve complex, verifiable tasks can be enhanced even when ge...
2025-06-02T00:00:00
no_new_dataset
false
0.71251
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24727
Xiaochen Zhang
Xiaochen Zhang and Haoyi Xiong
Knockoff-Guided Compressive Sensing: A Statistical Machine Learning Framework for Support-Assured Signal Recovery
null
null
null
null
stat.ML cs.LG eess.SP
http://creativecommons.org/publicdomain/zero/1.0/
This paper introduces a novel Knockoff-guided compressive sensing framework, referred to as \TheName{}, which enhances signal recovery by leveraging precise false discovery rate (FDR) control during the support identification phase. Unlike LASSO, which jointly performs support selection and signal estimation without ex...
2025-06-02T00:00:00
no_new_dataset
false
0.71148
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24728
Dongzi Jin
Dongzi Jin, Yong Xiao, Yingyu Li
Robust Federated Learning against Model Perturbation in Edge Networks
Accepted by IEEE ICC 2025
null
null
null
cs.LG cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated Learning (FL) is a promising paradigm for realizing edge intelligence, allowing collaborative learning among distributed edge devices by sharing models instead of raw data. However, the shared models are often assumed to be ideal, which would be inevitably violated in practice due to various perturbations, le...
2025-06-02T00:00:00
no_new_dataset
false
0.710632
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24729
Magamed Taimeskhanov
Magamed Taimeskhanov, Damien Garreau
Feature Attribution from First Principles
30 pages, 3 figures
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Feature attribution methods are a popular approach to explain the behavior of machine learning models. They assign importance scores to each input feature, quantifying their influence on the model's prediction. However, evaluating these methods empirically remains a significant challenge. To bypass this shortcoming, se...
2025-06-02T00:00:00
no_new_dataset
false
0.710865
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24731
Alan Sun
Alan Sun
Circuit Stability Characterizes Language Model Generalization
16 pages, 10 figures
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Extensively evaluating the capabilities of (large) language models is difficult. Rapid development of state-of-the-art models induce benchmark saturation, while creating more challenging datasets is labor-intensive. Inspired by the recent developments in mechanistic interpretability, we introduce circuit stability as a...
2025-06-02T00:00:00
no_new_dataset
false
0.708485
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24733
Jiaxu Zhang
Jiaxu Zhang, Xianfang Zeng, Xin Chen, Wei Zuo, Gang Yu, Guosheng Lin, Zhigang Tu
DreamDance: Animating Character Art via Inpainting Stable Gaussian Worlds
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents DreamDance, a novel character art animation framework capable of producing stable, consistent character and scene motion conditioned on precise camera trajectories. To achieve this, we re-formulate the animation task as two inpainting-based steps: Camera-aware Scene Inpainting and Pose-aware Video I...
2025-06-02T00:00:00
no_new_dataset
false
0.711625
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24735
Yu Hin (Gary) Au
Yu Hin Au and Levent Tun\c{c}el
A Computational Search for Minimal Obstruction Graphs for the Lov\'{a}sz--Schrijver SDP Hierarchy
null
null
null
null
math.CO cs.DM math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the lift-and-project relaxations of the stable set polytope of graphs generated by $\text{LS}_+$, the SDP lift-and-project operator devised by Lov\'{a}sz and Schrijver. In particular, we focus on searching for $\ell$-minimal graphs, which are graphs on $3\ell$ vertices whose stable set polytope has rank $\ell$...
2025-06-02T00:00:00
no_new_dataset
false
0.706275
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24736
Julio Cesar Cavalcanti
Julio Cesar Cavalcanti, Gabriel Skantze
"Dyadosyncrasy", Idiosyncrasy and Demographic Factors in Turn-Taking
Accepted to Interspeech 2025
null
null
null
eess.AS cs.CL
http://creativecommons.org/licenses/by/4.0/
Turn-taking in dialogue follows universal constraints but also varies significantly. This study examines how demographic (sex, age, education) and individual factors shape turn-taking using a large dataset of US English conversations (Fisher). We analyze Transition Floor Offset (TFO) and find notable interspeaker varia...
2025-06-02T00:00:00
no_new_dataset
false
0.704007
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24737
Erchi Wang
Erchi Wang, Yuqing Zhu, Yu-Xiang Wang
Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the problem of differentially private empirical risk minimization (DP-ERM) for binary linear classification. We obtain an efficient $(\varepsilon,\delta)$-DP algorithm with an empirical zero-one risk bound of $\tilde{O}\left(\frac{1}{\gamma^2\varepsilon n} + \frac{|S_{\mathrm{out}}|}{\gamma n}\right)...
2025-06-02T00:00:00
no_new_dataset
false
0.711735
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24740
Kalina Dimitrova
Kalina Dimitrova, Venelin Kozhuharov, Ruslan Nastaev and Peicho Petkov
Cluster Reconstruction in Electromagnetic Calorimeters Using Machine Learning Methods
null
null
null
null
physics.ins-det
http://creativecommons.org/licenses/by/4.0/
Machine-learning-based methods can be developed for the reconstruction of clusters in segmented detectors for high energy physics experiments. Convolutional neural networks with autoencoder architecture trained on labeled data from a simulated dataset reconstruct events by providing information about the hit point and ...
2025-06-02T00:00:00
no_new_dataset
false
0.712568
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24741
Alfonso M. Ganan-Calvo
Alfonso M. Ganan-Calvo and Miguel A. Herrada and Jens Eggers
Cone-jet Stokes solutions in strong viscous flows: the vanishing flow rate limit
38 pages, 15 figures, 1 appendix
null
null
null
physics.flu-dyn
http://creativecommons.org/licenses/by-nc-nd/4.0/
Steady tip streaming in the vanishing flow rate limit has been evidenced both experimentally and numerically in the literature. However, local conical Stokes flow solutions supporting these results at vanishing small scales around the emitting tip have remained elusive. This work presents approximate local conical solu...
2025-06-02T00:00:00
no_new_dataset
false
0.712639
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24742
Andres Munoz-Arcentales Ph. D.
Irene Plaza-Ortiz, Andres Munoz-Arcentales, Joaqu\'in Salvach\'ua, Carlos Aparicio, Gabriel Huecas, Enrique Barra
Authentication and authorization in Data Spaces: A relationship-based access control approach for policy specification based on ODRL
Accepted: OPAL 2025: ODRL And Beyond: Practical Applications And Challenges For Policy-Base Access And Usage Control., June 01--02, 2025, Portoro\v{z}, Slovenia
null
null
null
cs.CR cs.ET
http://creativecommons.org/licenses/by-nc-nd/4.0/
Data has become a crucial resource in the digital economy, fostering initiatives for secure and sovereign data sharing frameworks such as Data Spaces. However, these distributed environments require fine-grained access control mechanisms that balance openness with sovereignty and security. This paper proposes an extens...
2025-06-02T00:00:00
no_new_dataset
false
0.711695
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24746
Jiazhong Cen
Jiazhong Cen, Xudong Zhou, Jiemin Fang, Changsong Wen, Lingxi Xie, Xiaopeng Zhang, Wei Shen, Qi Tian
Tackling View-Dependent Semantics in 3D Language Gaussian Splatting
ICML 2025 camera ready. Project Page: https://jumpat.github.io/laga-page/
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recent advancements in 3D Gaussian Splatting (3D-GS) enable high-quality 3D scene reconstruction from RGB images. Many studies extend this paradigm for language-driven open-vocabulary scene understanding. However, most of them simply project 2D semantic features onto 3D Gaussians and overlook a fundamental gap between ...
2025-06-02T00:00:00
no_new_dataset
false
0.712592
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24751
Sangmin Kim
Sangmin Kim and Hae-Won Park
EL-AGHF: Extended Lagrangian Affine Geometric Heat Flow
6 pages, 4 figures
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
We propose a constrained Affine Geometric Heat Flow (AGHF) method that evolves so as to suppress the dynamics gaps associated with inadmissible control directions. AGHF provides a unified framework applicable to a wide range of motion planning problems, including both holonomic and non-holonomic systems. However, to ge...
2025-06-02T00:00:00
no_new_dataset
false
0.7127
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24754
Yingchaojie Feng
Yingchaojie Feng, Yiqun Sun, Yandong Sun, Minfeng Zhu, Qiang Huang, Anthony K. H. Tung, Wei Chen
Don't Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation
Accepted to ACL 2025
null
null
null
cs.CL cs.AI cs.IR
http://creativecommons.org/licenses/by/4.0/
In this work, we investigate an important task named instruction-following text embedding, which generates dynamic text embeddings that adapt to user instructions, highlighting specific attributes of text. Despite recent advancements, existing approaches suffer from significant computational overhead, as they require r...
2025-06-02T00:00:00
no_new_dataset
false
0.711039
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24756
Diego Clerissi
Dario Olianas, Diego Clerissi, Maurizio Leotta, Filippo Ricca
TESTQUEST: A Web Gamification Tool to Improve Locators and Page Objects Quality
4 pages, 3 figures, submitted to 51st Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA) 2025
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Web applications play a crucial role in our daily lives, making it essential to employ testing methods that ensure their quality. Typically, Web testing automation frameworks rely on locators to interact with the graphical user interface, acting as connection points to the elements on a Web page. Nevertheless, locators...
2025-06-02T00:00:00
no_new_dataset
false
0.709317
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24763
Steve Blandino
Steve Blandino, Nada Golmie, Anirudha Sahoo, Thao Nguyen, Tanguy Ropitault, David Griffith and Amala Sonny
Detecting Airborne Objects with 5G NR Radars
null
null
null
null
eess.SP cs.NI
http://creativecommons.org/licenses/by/4.0/
The integration of sensing capabilities into 5G New Radio (5G NR) networks offers an opportunity to enable the detection of airborne objects without the need for dedicated radars. This paper investigates the feasibility of using standardized Positioning Reference Signals (PRS) to detect UAVs in Urban Micro (UMi) and Ur...
2025-06-02T00:00:00
no_new_dataset
false
0.709798
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24768
Haoyu Li
Haoyu Li, Xuhong Li, Yiming Dong, Kun Liu
From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Dataset diversity plays a pivotal role for the successful training of many machine learning models, particularly in the supervised fine-tuning (SFT) stage of large language model (LLM) development. Despite increasing recognition of its importance, systematic analyses of dataset diversity still remain underexplored. To ...
2025-06-02T00:00:00
no_new_dataset
false
0.675912
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24776
Zachary Bastiani
Zachary Bastiani, Robert M. Kirby, Jacob Hochhalter, Shandian Zhe
Diffusion-Based Symbolic Regression
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Diffusion has emerged as a powerful framework for generative modeling, achieving remarkable success in applications such as image and audio synthesis. Enlightened by this progress, we propose a novel diffusion-based approach for symbolic regression. We construct a random mask-based diffusion and denoising process to ge...
2025-06-02T00:00:00
no_new_dataset
false
0.71144
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24780
RunZe He
Run-Ze He, Jun-Jian Su, Su-Juan Qin, Zheng-Ping Jin, Fei Gao
QGAN-based data augmentation for hybrid quantum-classical neural networks
null
null
null
null
cs.LG quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantum neural networks converge faster and achieve higher accuracy than classical models. However, data augmentation in quantum machine learning remains underexplored. To tackle data scarcity, we integrate quantum generative adversarial networks (QGANs) with hybrid quantum-classical neural networks (HQCNNs) to develop...
2025-06-02T00:00:00
no_new_dataset
false
0.712859
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24781
Karim Abou-Moustafa
Karim Abou-Moustafa
Efficient Estimation of Regularized Tyler's M-Estimator Using Approximate LOOCV
An extended version of a short article that appeared in 2023 IEEE Workshop on Information Theory, Saint-Malo, France
null
null
null
stat.ML cs.CE cs.CV cs.LG eess.SP
http://creativecommons.org/licenses/by/4.0/
We consider the problem of estimating a regularization parameter, or a shrinkage coefficient $\alpha \in (0,1)$ for Regularized Tyler's M-estimator (RTME). In particular, we propose to estimate an optimal shrinkage coefficient by setting $\alpha$ as the solution to a suitably chosen objective function; namely the leave...
2025-06-02T00:00:00
no_new_dataset
false
0.709143
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24784
Conor Heins
Conor Heins, Toon Van de Maele, Alexander Tschantz, Hampus Linander, Dimitrije Markovic, Tommaso Salvatori, Corrado Pezzato, Ozan Catal, Ran Wei, Magnus Koudahl, Marco Perin, Karl Friston, Tim Verbelen, Christopher Buckley
AXIOM: Learning to Play Games in Minutes with Expanding Object-Centric Models
10 pages main text, 4 figures, 2 tables; 25 pages supplementary material, 8 figures
null
null
null
cs.AI cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Current deep reinforcement learning (DRL) approaches achieve state-of-the-art performance in various domains, but struggle with data efficiency compared to human learning, which leverages core priors about objects and their interactions. Active inference offers a principled framework for integrating sensory information...
2025-06-02T00:00:00
no_new_dataset
false
0.709853
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24786
Eran Beeri Bamani
Eran Bamani Beeri, Eden Nissinman, Avishai Sintov
DiG-Net: Enhancing Quality of Life through Hyper-Range Dynamic Gesture Recognition in Assistive Robotics
arXiv admin note: substantial text overlap with arXiv:2411.18413
null
null
null
cs.RO cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
Dynamic hand gestures play a pivotal role in assistive human-robot interaction (HRI), facilitating intuitive, non-verbal communication, particularly for individuals with mobility constraints or those operating robots remotely. Current gesture recognition methods are mostly limited to short-range interactions, reducing ...
2025-06-02T00:00:00
no_new_dataset
false
0.711634
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24787
Yucheng Zhou
Yucheng Zhou, Jiahao Yuan, Qianning Wang
Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image Generation
null
null
null
null
cs.CV cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advancements in text-to-image (T2I) generation have enabled models to produce high-quality images from textual descriptions. However, these models often struggle with complex instructions involving multiple objects, attributes, and spatial relationships. Existing benchmarks for evaluating T2I models primarily fo...
2025-06-02T00:00:00
new_dataset
true
0.714777
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24788
Houjun Liu
Houjun Liu, John Bauer, Christopher D. Manning
Drop Dropout on Single-Epoch Language Model Pretraining
Accepted to ACL Findings; 5 pages, 2 figures, 4 pages of appendix
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Originally, dropout was seen as a breakthrough regularization technique that reduced overfitting and improved performance in almost all applications of deep learning by reducing overfitting. Yet, single-epoch pretraining tasks common to modern LLMs yield minimal overfitting, leading to dropout not being used for large ...
2025-06-02T00:00:00
no_new_dataset
false
0.710884
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24791
Jiaru Zhang
Jiaru Zhang, Juanwu Lu, Ziran Wang, Ruqi Zhang
Inference Acceleration of Autoregressive Normalizing Flows by Selective Jacobi Decoding
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Normalizing flows are promising generative models with advantages such as theoretical rigor, analytical log-likelihood computation, and end-to-end training. However, the architectural constraints to ensure invertibility and tractable Jacobian computation limit their expressive power and practical usability. Recent adva...
2025-06-02T00:00:00
no_new_dataset
false
0.712143
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24792
Xinliu Zhong
Xinliu Zhong, Leo Hwa Liang, Angela S. Koh, Yeo Si Yong
Lightweight Relational Embedding in Task-Interpolated Few-Shot Networks for Enhanced Gastrointestinal Disease Classification
6 pages, 15 figures
2024 IEEE Conference on Artificial Intelligence (CAI), 2024, 839-844
10.1109/CAI59869.2024.00157
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Traditional diagnostic methods like colonoscopy are invasive yet critical tools necessary for accurately diagnosing colorectal cancer (CRC). Detection of CRC at early stages is crucial for increasing patient survival rates. However, colonoscopy is dependent on obtaining adequate and high-quality endoscopic images. Prol...
2025-06-02T00:00:00
no_new_dataset
false
0.711128
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24800
Sergey Dyakov A.
Sergey A. Dyakov, Ilia A. Smagin, Natalia S. Salakhova, Oleg Blokhin, Denis G. Baranov, Ilia M. Fradkin, and Nikolay A. Gippius
Strong coupling of chiral light with chiral matter: a macroscopic study
12 pages, 4 figures
null
null
null
physics.optics cond-mat.other
http://creativecommons.org/licenses/by-nc-nd/4.0/
Maximizing the interaction between chiral light and chiral matter is pivotal for the advancement of technologies enabling optical detection that distinguishes between different handedness in chiral organic molecules. One strategy involves developing a resonator that sustains photonic modes with non-zero electromagnetic...
2025-06-02T00:00:00
no_new_dataset
false
0.713985
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24801
Dorian Christoph Quelle
Dorian Quelle, Frederic Denker, Prashant Garg, Alexandre Bovet
Why Academics Are Leaving Twitter for Bluesky
null
null
null
null
cs.SI cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We analyse the migration of 300,000 academic users from Twitter/X to Bluesky between 2023 and early 2025, combining rich bibliometric data, longitudinal social-media activity, and a novel cross-platform identity-matching pipeline. We show that 18% of scholars in our sample transitioned, with transition rates varying sh...
2025-06-02T00:00:00
no_new_dataset
false
0.708169
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24802
John Stephan
Marc Gonz\'alez, Rachid Guerraoui, Rafael Pinot, Geovani Rizk, John Stephan, Fran\c{c}ois Ta\"iani
ByzFL: Research Framework for Robust Federated Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present ByzFL, an open-source Python library for developing and benchmarking robust federated learning (FL) algorithms. ByzFL provides a unified and extensible framework that includes implementations of state-of-the-art robust aggregators, a suite of configurable attacks, and tools for simulating a variety of FL sce...
2025-06-02T00:00:00
no_new_dataset
false
0.708566
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24804
Xuhui Zhang
Chunjie Wang and Xuhui Zhang and Wenchao Liu and Jinke Ren and Huijun Xing and Shuqiang Wang and Yanyan Shen
Coordinated Beamforming for RIS-Empowered ISAC Systems over Secure Low-Altitude Networks
This manuscript has been submitted to the IEEE
null
null
null
eess.SP cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Emerging as a cornerstone for next-generation wireless networks, integrated sensing and communication (ISAC) systems demand innovative solutions to balance spectral efficiency and sensing accuracy. In this paper, we propose a coordinated beamforming framework for a reconfigurable intelligent surface (RIS)-empowered ISA...
2025-06-02T00:00:00
no_new_dataset
false
0.711438
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24805
Hernan Haimovich
Hernan Haimovich, Shenyu Liu, Antonio Russo, Jose L. Mancilla-Aguilar
Input-Power-to-State Stability of Time-Varying Systems
Submitted to Automatica
null
null
null
eess.SY cs.SY math.OC
http://creativecommons.org/licenses/by-nc-nd/4.0/
When the state of a system may remain bounded even if both the input amplitude and energy are unbounded, then the state bounds given by the standard input-to-state stability (ISS) and integral-ISS (iISS) properties may provide no useful information. This paper considers an ISS-related concept suitable in such a case: i...
2025-06-02T00:00:00
no_new_dataset
false
0.711487
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24806
Ahmadreza Montazerolghaem
Somaye Imanpour, Ahmadreza Montazerolghaem, Saeed Afshari
Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
The Internet of Multimedia Things (IoMT) represents a significant advancement in the evolution of IoT technologies, focusing on the transmission and management of multimedia streams. As the volume of data continues to surge and the number of connected devices grows exponentially, internet traffic has reached unpreceden...
2025-06-02T00:00:00
no_new_dataset
false
0.711591
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24807
Maksim Kulichenko
Vishikh Athavale, Nikita Fedik, William Colglazier, Anders M. N. Niklasson, Maksim Kulichenko, Sergei Tretiak
PySEQM 2.0: Accelerated Semiempirical Excited State Calculations on Graphical Processing Units
null
null
null
LA-UR-25-25101
physics.chem-ph physics.comp-ph
http://creativecommons.org/licenses/by-nc-nd/4.0/
We report the implementation of electronic excited states for semi-empirical quantum chemical methods at the configuration interaction singles (CIS) and time-dependent Hartree-Fock (TDHF) level of theory in the PySEQM software. Built on PyTorch, this implementation leverages GPU acceleration to significantly speed up m...
2025-06-02T00:00:00
no_new_dataset
false
0.709252
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24808
Wenhao Ding
Wenhao Ding, Sushant Veer, Yuxiao Chen, Yulong Cao, Chaowei Xiao, Marco Pavone
RealDrive: Retrieval-Augmented Driving with Diffusion Models
null
null
null
null
cs.RO cs.AI
http://creativecommons.org/licenses/by/4.0/
Learning-based planners generate natural human-like driving behaviors by learning to reason about nuanced interactions from data, overcoming the rigid behaviors that arise from rule-based planners. Nonetheless, data-driven approaches often struggle with rare, safety-critical scenarios and offer limited controllability ...
2025-06-02T00:00:00
no_new_dataset
false
0.712054
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24812
Marcelo Fiore
Marcelo Fiore and Sanjiv Ranchod
Substructural Abstract Syntax with Variable Binding and Single-Variable Substitution
To appear in the Fortieth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS'25)
null
null
null
cs.LO math.CT
http://creativecommons.org/licenses/by/4.0/
We develop a unified categorical theory of substructural abstract syntax with variable binding and single-variable (capture-avoiding) substitution. This is done for the gamut of context structural rules given by exchange (linear theory) with weakening (affine theory) or with contraction (relevant theory) and with both ...
2025-06-02T00:00:00
no_new_dataset
false
0.708634
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24813
Marc Barthelemy
Yannick Feld, Marc Barthelemy
Critical demand in a stochastic model of flows in supply networks
Letter (5 pages with 4 figures)+Supplementary Material
Phys. Rev. Lett. 134, 217401 (Published 30 May, 2025)
null
null
physics.soc-ph cond-mat.dis-nn cond-mat.stat-mech
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Supply networks are essential for modern production, yet their critical properties remain understudied. We present a stochastic model with random production capacities to analyze material flow to a root node, focusing on topology and buffer stocks. The critical demand, where unsatisfied demand diverges, is examined mos...
2025-06-02T00:00:00
no_new_dataset
false
0.710995
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24814
Sarah Kostinski
Debendro Mookerjee and Sarah Kostinski
Closed-form survival probabilities for biased random walks at arbitrary step number
null
null
null
null
cond-mat.stat-mech physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a closed-form expression for the survival probability of a biased random walker to first reach a target site on a 1D lattice. The expression holds for any step number $N$ and is computationally faster than non-closed-form results in the literature. Because our result is exact even in the intermediate step nu...
2025-06-02T00:00:00
no_new_dataset
false
0.711256
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24815
V Varagapriya
V Varagapriya, Vikas Vikram Singh, Abdel Lisser
Convex Approximations of Random Constrained Markov Decision Processes
null
null
null
null
math.OC cs.SY eess.SY
http://creativecommons.org/licenses/by-nc-nd/4.0/
Constrained Markov decision processes (CMDPs) are used as a decision-making framework to study the long-run performance of a stochastic system. It is well-known that a stationary optimal policy of a CMDP problem under discounted cost criterion can be obtained by solving a linear programming problem when running costs a...
2025-06-02T00:00:00
no_new_dataset
false
0.711597
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24816
Jiangpeng He
Jiangpeng He and Zhihao Duan and Fengqing Zhu
CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning
Accepted to CVPR 2025
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Class-Incremental Learning (CIL) aims to learn new classes sequentially while retaining the knowledge of previously learned classes. Recently, pre-trained models (PTMs) combined with parameter-efficient fine-tuning (PEFT) have shown remarkable performance in rehearsal-free CIL without requiring exemplars from previous ...
2025-06-02T00:00:00
no_new_dataset
false
0.710664
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24817
Eric Nelson
Eric C. Nelson, Kyle J. Charbonnet, Haytham H. Effarah, Trevor Reutershan, Kyle D. Chesnut, Christopher P. J. Barty
Focused axisymmetric spatially chirped beams
12 pages, supplemental document (3 pages), submitted for peer review
null
null
null
physics.optics
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A characterization of the focused space-time structures of radially chirped beams is provided, detailing different tunable properties such as: variable on-axis centroid velocity, symmetric pulse front tilt, transverse intensity modulations, and polarization states. While the practical generation of ideal radially chirp...
2025-06-02T00:00:00
no_new_dataset
false
0.712346
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24818
Dirk Witthaut
Aarathi Parameswaran, Iva Ba\v{c}i\'c, Andrea Benigni, Dirk Witthaut
Symmetry breaking in minimum dissipation networks
12 pages, 11 figures
null
null
null
nlin.AO physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Both natural and man-made supply networks exhibit universal structural patterns, such as the formation of loops. These patterns can be understood in terms of optimization models, assuming that biological networks evolved to optimal states and technical networks are designed to function optimally. In this article, we an...
2025-06-02T00:00:00
no_new_dataset
false
0.712625
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24819
Haozhan Tang
Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson, Weiming Zhi
Bi-Manual Joint Camera Calibration and Scene Representation
null
null
null
null
cs.RO cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Robot manipulation, especially bimanual manipulation, often requires setting up multiple cameras on multiple robot manipulators. Before robot manipulators can generate motion or even build representations of their environments, the cameras rigidly mounted to the robot need to be calibrated. Camera calibration is a cumb...
2025-06-02T00:00:00
no_new_dataset
false
0.711953
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24820
Yu Xi
Yu Xi, Xiaoyu Gu, Haoyu Li, Jun Song, Bo Zheng, Kai Yu
Masked Self-distilled Transducer-based Keyword Spotting with Semi-autoregressive Decoding
null
null
null
null
cs.SD eess.AS
http://creativecommons.org/licenses/by/4.0/
RNN-T-based keyword spotting (KWS) with autoregressive decoding~(AR) has gained attention due to its streaming architecture and superior performance. However, the simplicity of the prediction network in RNN-T poses an overfitting issue, especially under challenging scenarios, resulting in degraded performance. In this ...
2025-06-02T00:00:00
no_new_dataset
false
0.711271
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24823
Yinggan Xu
Yinggan Xu, Yue Liu, Zhiqiang Gao, Changnan Peng and Di Luo
PhySense: Principle-Based Physics Reasoning Benchmarking for Large Language Models
null
null
null
null
cs.LG cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) have rapidly advanced and are increasingly capable of tackling complex scientific problems, including those in physics. Despite this progress, current LLMs often fail to emulate the concise, principle-based reasoning characteristic of human experts, instead generating lengthy and opaque sol...
2025-06-02T00:00:00
new_dataset
true
0.712242
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24824
Marta L\'opez Rauhut
Marta L\'opez-Rauhut, Hongyu Zhou, Mathieu Aubry, Loic Landrieu
Segmenting France Across Four Centuries
20 pages, 8 figures, 3 tables
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Historical maps offer an invaluable perspective into territory evolution across past centuries--long before satellite or remote sensing technologies existed. Deep learning methods have shown promising results in segmenting historical maps, but publicly available datasets typically focus on a single map type or period, ...
2025-06-02T00:00:00
new_dataset
true
0.710998
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24831
Luis Enrique Correa Rocha Prof
Ruixue Jing, Ryota Kobayashi, Luis Enrique Correa Rocha
Optimising cryptocurrency portfolios through stable clustering of price correlation networks
Comments welcomed
null
null
null
physics.pop-ph physics.soc-ph q-fin.PM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The emerging cryptocurrency market presents unique challenges for investment due to its unregulated nature and inherent volatility. However, collective price movements can be explored to maximise profits with minimal risk using investment portfolios. In this paper, we develop a technical framework that utilises histori...
2025-06-02T00:00:00
no_new_dataset
false
0.712298
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24833
Duxing Hao
Duxing Hao, Chun-I Lu, Ziqi Sun, Yu-Chen Chang, Wen-Hao Chang, Ye-Ru Chen, Akiyoshi Park, Beining Rao, Siyuan Qiu, Yann-Wen Lan, Ting-Hua Lu, and Nai-Chang Yeh
Cryogenic scanning photocurrent spectroscopy for materials responses to structured optical fields
null
null
null
null
cond-mat.other physics.ins-det
http://creativecommons.org/licenses/by-nc-sa/4.0/
Circular dichroism spectroscopy is known to provide important insights into the interplay of different degrees of freedom in quantum materials, and yet spectroscopic study of the optoelectronic responses of quantum materials to structured optical fields, such as light with finite spin and orbital angular momentum, has ...
2025-06-02T00:00:00
no_new_dataset
false
0.710208
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24837
Qizao Wang
Yinglian Zhu, Haiyang Yu, Qizao Wang, Wei Lu, Xiangyang Xue, Bin Li
Zero-Shot Chinese Character Recognition with Hierarchical Multi-Granularity Image-Text Aligning
The first three authors contributed equally
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Chinese Character Recognition (CCR) is a fundamental technology for intelligent document processing. Unlike Latin characters, Chinese characters exhibit unique spatial structures and compositional rules, allowing for the use of fine-grained semantic information in representation. However, existing approaches are usuall...
2025-06-02T00:00:00
no_new_dataset
false
0.711496
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24839
Shilpa Sarkar
Shilpa Sarkar
Novel methodology to obtain transonic solutions for dissipative flows around compact objects
18 pages, 10 figures, 1 table, Accepted in Physical Review D after minor revision
null
null
null
astro-ph.HE hep-th physics.comp-ph physics.plasm-ph
http://creativecommons.org/licenses/by/4.0/
A novel methodology to obtain global transonic solutions around compact objects is reported here. A unified methodology to obtain accretion as well as wind solutions around these objects has been presented. Flows around compact objects are dissipative, and the conservation equations are therefore stiff. In such conditi...
2025-06-02T00:00:00
no_new_dataset
false
0.713103
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24840
Yuan Qing
Yuwen Tan, Yuan Qing, Boqing Gong
Vision LLMs Are Bad at Hierarchical Visual Understanding, and LLMs Are the Bottleneck
28 pages, 13 figures
null
null
null
cs.CV cs.AI cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper reveals that many state-of-the-art large language models (LLMs) lack hierarchical knowledge about our visual world, unaware of even well-established biology taxonomies. This shortcoming makes LLMs a bottleneck for vision LLMs' hierarchical visual understanding (e.g., recognizing Anemone Fish but not Vertebra...
2025-06-02T00:00:00
no_new_dataset
false
0.708804
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24844
Wanyun Xie
Wanyun Xie, Francesco Tonin, Volkan Cevher
Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning
ICML 2025
null
null
null
cs.LG cs.CL
http://creativecommons.org/licenses/by/4.0/
Training data mixtures greatly impact the generalization performance of large language models. Existing domain reweighting methods often rely on costly weight computations and require retraining when new data is introduced. To this end, we introduce a flexible and efficient data mixing framework, Chameleon, that employ...
2025-06-02T00:00:00
no_new_dataset
false
0.711774
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24849
Mauro Pastore
Jean Barbier, Francesco Camilli, Minh-Toan Nguyen, Mauro Pastore, Rudy Skerk
Statistical mechanics of extensive-width Bayesian neural networks near interpolation
9 pages + appendices, 12 figures. This submission supersedes arXiv:2501.18530
null
null
null
stat.ML cond-mat.dis-nn cond-mat.stat-mech cs.IT cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For three decades statistical mechanics has been providing a framework to analyse neural networks. However, the theoretically tractable models, e.g., perceptrons, random features models and kernel machines, or multi-index models and committee machines with few neurons, remained simple compared to those used in applicat...
2025-06-02T00:00:00
no_new_dataset
false
0.712227
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24853
Zhao Mandi
Zhao Mandi, Yifan Hou, Dieter Fox, Yashraj Narang, Ajay Mandlekar, Shuran Song
DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
null
null
null
null
cs.RO cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
We study the problem of functional retargeting: learning dexterous manipulation policies to track object states from human hand-object demonstrations. We focus on long-horizon, bimanual tasks with articulated objects, which is challenging due to large action space, spatiotemporal discontinuities, and embodiment gap bet...
2025-06-02T00:00:00
new_dataset
true
0.713744
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24857
Heli Ben-Hamu
Heli Ben-Hamu, Itai Gat, Daniel Severo, Niklas Nolte, Brian Karrer
Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent masked diffusion models (MDMs) have shown competitive performance compared to autoregressive models (ARMs) for language modeling. While most literature has focused on performance enhancing sampling procedures, efficient sampling from MDMs has been scarcely explored. We make the observation that often a given seq...
2025-06-02T00:00:00
no_new_dataset
false
0.709917
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24860
Victoria Webster-Wood
Avery S. Williamson, Michael J. Bennington, Ravesh Sukhnandan, Mrinali Nakhre, Yuemin Mao, Victoria A. Webster-Wood
PB&J: Peanut Butter and Joints for Damped Articulation
to be published in Living Machines 2025 Proceedings
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many bioinspired robots mimic the rigid articulated joint structure of the human hand for grasping tasks, but experience high-frequency mechanical perturbations that can destabilize the system and negatively affect precision without a high-frequency controller. Despite having bandwidth-limited controllers that experien...
2025-06-02T00:00:00
no_new_dataset
false
0.70082
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24863
Junyu Zhang
Junyu Zhang, Runpei Dong, Han Wang, Xuying Ning, Haoran Geng, Peihao Li, Xialin He, Yutong Bai, Jitendra Malik, Saurabh Gupta, Huan Zhang
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents AlphaOne ($\alpha$1), a universal framework for modulating reasoning progress in large reasoning models (LRMs) at test time. $\alpha$1 first introduces $\alpha$ moment, which represents the scaled thinking phase with a universal parameter $\alpha$. Within this scaled pre-$\alpha$ moment phase, it dy...
2025-06-02T00:00:00
no_new_dataset
false
0.710496
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24864
Shizhe Diao
Mingjie Liu, Shizhe Diao, Ximing Lu, Jian Hu, Xin Dong, Yejin Choi, Jan Kautz, Yi Dong
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
26 pages, 17 figures
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in reasoning-centric language models have highlighted reinforcement learning (RL) as a promising method for aligning models with verifiable rewards. However, it remains contentious whether RL truly expands a model's reasoning capabilities or merely amplifies high-reward outputs already latent in the bas...
2025-06-02T00:00:00
no_new_dataset
false
0.709828
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24867
Mukul Ranjan
Ujjwal Upadhyay and Mukul Ranjan and Zhiqiang Shen and Mohamed Elhoseiny
Time Blindness: Why Video-Language Models Can't See What Humans Can?
Project page at https://timeblindness.github.io/
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Recent advances in vision-language models (VLMs) have made impressive strides in understanding spatio-temporal relationships in videos. However, when spatial information is obscured, these models struggle to capture purely temporal patterns. We introduce $\textbf{SpookyBench}$, a benchmark where information is encoded ...
2025-06-02T00:00:00
new_dataset
true
0.660718
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24873
Bojia Zi
Bojia Zi, Weixuan Peng, Xianbiao Qi, Jianan Wang, Shihao Zhao, Rong Xiao, Kam-Fai Wong
MiniMax-Remover: Taming Bad Noise Helps Video Object Removal
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recent advances in video diffusion models have driven rapid progress in video editing techniques. However, video object removal, a critical subtask of video editing, remains challenging due to issues such as hallucinated objects and visual artifacts. Furthermore, existing methods often rely on computationally expensive...
2025-06-02T00:00:00
no_new_dataset
false
0.713024
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24874
Adam Stein
Adam Stein, Aaditya Naik, Neelay Velingker, Mayur Naik, Eric Wong
The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models
19 pages, 11 figures
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Neuro-symbolic learning was proposed to address challenges with training neural networks for complex reasoning tasks with the added benefits of interpretability, reliability, and efficiency. Neuro-symbolic learning methods traditionally train neural models in conjunction with symbolic programs, but they face significan...
2025-06-02T00:00:00
no_new_dataset
false
0.713314
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24876
Tajamul Ashraf
Tajamul Ashraf, Amal Saqib, Hanan Ghani, Muhra AlMahri, Yuhao Li, Noor Ahsan, Umair Nawaz, Jean Lahoud, Hisham Cholakkal, Mubarak Shah, Philip Torr, Fahad Shahbaz Khan, Rao Muhammad Anwer, Salman Khan
Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks
null
null
null
null
cs.CV cs.CL
http://creativecommons.org/licenses/by/4.0/
Deep reasoning is fundamental for solving complex tasks, especially in vision-centric scenarios that demand sequential, multimodal understanding. However, existing benchmarks typically evaluate agents with fully synthetic, single-turn queries, limited visual modalities, and lack a framework to assess reasoning quality ...
2025-06-02T00:00:00
new_dataset
true
0.711932
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24877
Yangyi Huang
Yangyi Huang and Ye Yuan and Xueting Li and Jan Kautz and Umar Iqbal
AdaHuman: Animatable Detailed 3D Human Generation with Compositional Multiview Diffusion
Website: https://nvlabs.github.io/AdaHuman
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing methods for image-to-3D avatar generation struggle to produce highly detailed, animation-ready avatars suitable for real-world applications. We introduce AdaHuman, a novel framework that generates high-fidelity animatable 3D avatars from a single in-the-wild image. AdaHuman incorporates two key innovations: (1...
2025-06-02T00:00:00
no_new_dataset
false
0.712166
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2505.24878
Yaxin Luo
Yaxin Luo, Zhaoyi Li, Jiacheng Liu, Jiacheng Cui, Xiaohan Zhao, Zhiqiang Shen
Open CaptchaWorld: A Comprehensive Web-based Platform for Testing and Benchmarking Multimodal LLM Agents
Code at: https://github.com/MetaAgentX/OpenCaptchaWorld
null
null
null
cs.AI cs.CL cs.CV cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
CAPTCHAs have been a critical bottleneck for deploying web agents in real-world applications, often blocking them from completing end-to-end automation tasks. While modern multimodal LLM agents have demonstrated impressive performance in static perception tasks, their ability to handle interactive, multi-step reasoning...
2025-06-02T00:00:00
new_dataset
true
0.702896
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1810.06981
Christian Baumgarten
C. Baumgarten
How to (Un-) Quantum Mechanics
35 Pages, 1 Figure
null
null
null
physics.gen-ph quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When compared to quantum mechanics, classical mechanics is often depicted in a specific metaphysical flavour: spatio-temporal realism or a Newtonian "background" is presented as an intrinsic fundamental classical presumption. However, the Hamiltonian formulation of classical analytical mechanics is based on abstract ge...
2025-05-30T00:00:00
no_new_dataset
false
0.710126
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
1911.11868
Greg Bodwin
Greg Bodwin and Santosh Vempala
A Unified View of Graph Regularity via Matrix Decompositions
null
null
null
null
cs.DS math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We prove algorithmic weak and \Szemeredi{} regularity lemmas for several classes of sparse graphs in the literature, for which only weak regularity lemmas were previously known. These include core-dense graphs, low threshold rank graphs, and (a version of) $L^p$ upper regular graphs. More precisely, we define \emph{cut...
2025-05-30T00:00:00
no_new_dataset
false
0.707962
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2001.07495
Daniel Nissani
Daniel N. Nissani (Nissensohn)
Unsupervisedly Learned Representations: Should the Quest be Over?
published at The 6th International Conference on Machine Learning, Optimization and Data Science - LOD 2020
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
After four decades of research there still exists a Classification accuracy gap of about 20% between our best Unsupervisedly Learned Representations methods and the accuracy rates achieved by intelligent animals. It thus may well be that we are looking in the wrong direction. A possible solution to this puzzle is prese...
2025-05-30T00:00:00
no_new_dataset
false
0.709158
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2007.13121
Sahil Singla
Danny Segev and Sahil Singla
Efficient Approximation Schemes for Stochastic Probing and Selection-Stopping Problems
38 pages; the preliminary version appeared in EC 2021
null
null
null
cs.DS cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a general framework to design {efficient} polynomial time approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization problems. Given an error parameter $\epsilon>0$, such algorithmic schemes attain a $(1-\epsilon)$-approximation in $t(\epsilon)\cdot poly(|{\cal I}|)$ t...
2025-05-30T00:00:00
no_new_dataset
false
0.709779
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2111.00814
Tamas Spisak
Tamas Spisak
Statistical quantification of confounding bias in predictive modelling
20 pages, 7 figures. The manuscript is associated with the the python package `mlconfound`: https://mlconfound.readthedocs.io See manuscript repository, including fully reproducible analysis code, here: https://github.com/pni-lab/mlconfound-manuscript
GigaScience, Volume 11, 2022, giac082
10.1093/gigascience/giac082
null
cs.LG q-bio.QM stat.ML
http://creativecommons.org/licenses/by/4.0/
The lack of non-parametric statistical tests for confounding bias significantly hampers the development of robust, valid and generalizable predictive models in many fields of research. Here I propose the partial and full confounder tests, which, for a given confounder variable, probe the null hypotheses of unconfounded...
2025-05-30T00:00:00
no_new_dataset
false
0.711734
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2111.12835
Cody Christopher PhD
Cody James Christopher, Kristen Moore, David Liebowitz
SchemaDB: Structures in Relational Datasets
Draft
Comm.Comp.Inf.Sci (CCIS). 1741 (2022) AusDM. 233-243
10.1007/978-981-19-8746-5_17
null
cs.DB cs.LG
http://creativecommons.org/licenses/by/4.0/
In this paper we introduce the SchemaDB data-set; a collection of relational database schemata in both sql and graph formats. Databases are not commonly shared publicly for reasons of privacy and security, so schemata are not available for study. Consequently, an understanding of database structures in the wild is lack...
2025-05-30T00:00:00
new_dataset
true
0.67
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2203.02252
Qiang Zou
Qiang Zou
Parametric/direct CAD integration
12 pages; 3 figures
Computer-Aided Design 157 (2023): 103465
10.1016/j.cad.2022.103465
null
cs.GR cs.CG
http://creativecommons.org/licenses/by-nc-nd/4.0/
In the history of computer-aided design (CAD), feature-based parametric modeling and boundary representation-based direct modeling are two of the most important CAD paradigms, developed respectively in the late 1980s and the late 2000s. They have complementary advantages and limitations, thereby offering huge potential...
2025-05-30T00:00:00
no_new_dataset
false
0.711932
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2204.07971
Jelena Stratijev
Milo\v{s} Stojakovi\'c and Jelena Stratijev
On strong avoiding games
23 pages
Discrete Mathematics 346 (2023) 113270
10.1016/j.disc.2022.113270
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given an increasing graph property $\cal F$, the strong Avoider-Avoider $\cal F$ game is played on the edge set of a complete graph. Two players, Red and Blue, take turns in claiming previously unclaimed edges with Red going first, and the player whose graph possesses $\cal F$ first loses the game. If the property $\ca...
2025-05-30T00:00:00
no_new_dataset
false
0.709546
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2207.00378
Micha{\l} Siemaszko
Micha{\l} Siemaszko, Adam Buraczewski, Bertrand Le Saux, Magdalena Stobi\'nska
Rapid training of quantum recurrent neural networks
null
Quantum Mach. Intell. 5, 31 (2023)
10.1007/s42484-023-00117-0
5 (31)
quant-ph cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Time series prediction is essential for human activities in diverse areas. A common approach to this task is to harness Recurrent Neural Networks (RNNs). However, while their predictions are quite accurate, their learning process is complex and, thus, time and energy consuming. Here, we propose to extend the concept of...
2025-05-30T00:00:00
no_new_dataset
false
0.712435
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2209.06725
Takase Shimizu
Takase Shimizu, Jun-ichiro Ohe, Akira Endo, Taketomo Nakamura, and Shingo Katsumoto
Half-mirror for electrons on quantum Hall copropagating edge channels
null
Phys. Rev. Applied 19, 034085 (2023)
10.1103/PhysRevApplied.19.034085
null
cond-mat.mes-hall physics.app-ph quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A half-mirror that divides a spin-polarized electron into two parallel copropagating spin-resolved quantum Hall edge channels one half each is presented in this study. The partition process was coherent, as confirmed by observing the Aharonov-Bohm oscillation at a high visibility of up to 60% in a Mach-Zehnder interfer...
2025-05-30T00:00:00
no_new_dataset
false
0.712092
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2210.15709
Gunnar K\"onig
Gunnar K\"onig, Timo Freiesleben, Moritz Grosse-Wentrup
Improvement-Focused Causal Recourse (ICR)
under review
null
10.1609/aaai.v37i10.26398
null
stat.ML cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
Algorithmic recourse recommendations, such as Karimi et al.'s (2021) causal recourse (CR), inform stakeholders of how to act to revert unfavourable decisions. However, some actions lead to acceptance (i.e., revert the model's decision) but do not lead to improvement (i.e., may not revert the underlying real-world state...
2025-05-30T00:00:00
no_new_dataset
false
0.712262
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2301.08028
Jacob Beck
Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa Zintgraf, Chelsea Finn, Shimon Whiteson
A Tutorial on Meta-Reinforcement Learning
Published in Foundations and Trends in Machine Learning as "A Tutorial on Meta-Reinforcement Learning". For the earlier version titled "A Survey of Meta-Reinforcement Learning", see v3 in the submission history at arXiv:2301.08028v3
Foundations and Trends in Machine Learning: Vol. 18, No. 2-3, pp 224-384 (2025)
10.1561/2200000080
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
While deep reinforcement learning (RL) has fueled multiple high-profile successes in machine learning, it is held back from more widespread adoption by its often poor data efficiency and the limited generality of the policies it produces. A promising approach for alleviating these limitations is to cast the development...
2025-05-30T00:00:00
no_new_dataset
false
0.711847
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2302.04363
Alexander Jung
S. Abdurakhmanova, Y. SarcheshmehPour and A. Jung
Plug In and Learn: Federated Intelligence over a Smart Grid of Models
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We present a model-agnostic federated learning method that mirrors the operation of a smart power grid: diverse local models, like energy prosumers, train independently on their own data while exchanging lightweight signals to coordinate with statistically similar peers. This coordination is governed by a graph-based r...
2025-05-30T00:00:00
no_new_dataset
false
0.710025
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2303.09117
Weixing Chen
Weixing Chen, Yang Liu, Ce Wang, Jiarui Zhu, Guanbin Li, Cheng-Lin Liu and Liang Lin
Cross-Modal Causal Intervention for Medical Report Generation
Accepted by IEEE TIP 2025, 16 pages, 11 figures, 7 tables
IEEE Transactions on Image Processing 34 (2025) 2970-2985
10.1109/TIP.2025.3568746
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Radiology Report Generation (RRG) is essential for computer-aided diagnosis and medication guidance, which can relieve the heavy burden of radiologists by automatically generating the corresponding radiology reports according to the given radiology image. However, generating accurate lesion descriptions remains challen...
2025-05-30T00:00:00
no_new_dataset
false
0.712222
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2305.03112
Lechao Cheng
Lechao Cheng, Zerun Liu, Jingxuan He, Chaowei Fang, Dingwen Zhang, Meng Wang
Calibrating Undisciplined Over-Smoothing in Transformer for Weakly Supervised Semantic Segmentation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Weakly supervised semantic segmentation (WSSS) has recently attracted considerable attention because it requires fewer annotations than fully supervised approaches, making it especially promising for large-scale image segmentation tasks. Although many vision transformer-based methods leverage self-attention affinity ma...
2025-05-30T00:00:00
no_new_dataset
false
0.711815
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
2306.17159
Jean-Philip Piquemal
C\'esar Feniou, Muhammad Hassan, Baptiste Claudon, Axel Courtat, Olivier Adjoua, Yvon Maday, Jean-Philip Piquemal
Greedy Gradient-free Adaptive Variational Quantum Algorithms on a Noisy Intermediate Scale Quantum Computer
null
Scientific Reports, 2025, 15, 18689
10.1038/s41598-025-99962-1
null
quant-ph physics.chem-ph
http://creativecommons.org/licenses/by/4.0/
Hybrid quantum-classical adaptive Variational Quantum Eigensolvers (VQE) hold the potential to outperform classical computing for simulating many-body quantum systems. However, practical implementations on current quantum processing units (QPUs) are challenging due to the noisy evaluation of a polynomially scaling numb...
2025-05-30T00:00:00
no_new_dataset
false
0.709817
2026-03-01T00:45:07.287856
davanstrien/ModernBERT-base-is-new-arxiv-dataset
End of preview. Expand in Data Studio
README.md exists but content is empty.
Downloads last month
4