Papers
Research papers from arXiv and related sources
AoE: Always-on Egocentric Human Video Collection for Embodied AI
Embodied foundation models require large-scale, high-quality real-world interaction data for pre-training and scaling. However, existing data collection methods suffer from high infrastructure cost...
Bowen Yang, Zishuo Li, Yang Sun, Changtao Miao, Yifan Yang, Man Luo, Xiaotong Yan, Feng Jiang, Ji...
Optimization-Based Behavioral Modeling of Mixers for Frequency Comb OFDM Radar Processing
This paper presents an optimization-based behavioral model for mixers driven by multi-tone local oscillator (LO) signals, considered specifically for frequency comb orthogonal frequency-division mu...
Umut Utku Erdem, Henning Poensgen, Taewon Jeong, Lucas Giroto, Benjamin Nuss, Ibrahim Kagan Aksoy...
Characterization of Josephson Junction Aging and Annealing Under Different Environments
Understanding the aging behavior of Josephson junctions and the effect of annealing on junction resistances is important in building large-scale superconducting quantum processors. Here we study th...
Rangga P. Budoyo, Rasanayagam S. Kajen, Bing Wen Cheah, Long H. Nguyen, Rainer Dumke
LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding
Speculative decoding accelerates autoregressive large language model (LLM) inference by using a lightweight draft model to propose candidate tokens that are then verified in parallel by the target ...
Alexander Samarin, Sergei Krutikov, Anton Shevtsov, Sergei Skvortsov, Filipp Fisin, Alexander Gol...
RF-Agent: Automated Reward Function Design via Language Agent Tree Search
Designing efficient reward functions for low-level control tasks is a challenging problem. Recent research aims to reduce reliance on expert experience by using Large Language Models (LLMs) with ta...
Ning Gao, Xiuhui Zhang, Xingyu Jiang, Mukang You, Mohan Zhang, Yue Deng
SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale
Software engineering agents (SWE) are improving rapidly, with recent gains largely driven by reinforcement learning (RL). However, RL training is constrained by the scarcity of large-scale task col...
Ibragim Badertdinov, Maksim Nekrashevich, Anton Shevtsov, Alexander Golubev
RUMAD: Reinforcement-Unifying Multi-Agent Debate
Multi-agent debate (MAD) systems leverage collective intelligence to enhance reasoning capabilities, yet existing approaches struggle to simultaneously optimize accuracy, consensus formation, and c...
Chao Wang, Han Lin, Huaze Tang, Huijing Lin, Wenbo Ding
NAU-QMUL: Utilizing BERT and CLIP for Multi-modal AI-Generated Image Detection
With the aim of detecting AI-generated images and identifying the specific models responsible for their generation, we propose a multi-modal multi-task model. The model leverages pre-trained BERT a...
Xiaoyu Guo, Arkaitz Zubiaga
A Fast Heuristic for Stochastic Steiner Tree Problems
Network design under uncertainty arises in countless real-world settings and can be captured by the Stochastic Steiner Tree Problem (SSTP). Although there are a few approaches specifically tailored...
Berend Markhorst, Alessandro Zocca, Joost Berkhout, Rob van der Mei
CLFEC: A New Task for Unified Linguistic and Factual Error Correction in paragraph-level Chinese Professional Writing
Chinese text correction has traditionally focused on spelling and grammar, while factual error correction is usually treated separately. However, in paragraph-level Chinese professional writing, li...
Jian Kai, Zidong Zhang, Jiwen Chen, Zhengxiang Wu, Songtao Sun, Fuyang Li, Yang Cao, Qiang Liu
OmniXtreme: Breaking the Generality Barrier in High-Dynamic Humanoid Control
High-fidelity motion tracking serves as the ultimate litmus test for generalizable, human-level motor skills. However, current policies often hit a "generality barrier": as motion libraries scale i...
Yunshen Wang, Shaohang Zhu, Peiyuan Zhi, Yuhan Li, Jiaxin Li, Yong-Lu Li, Yuchen Xiao, Xingxing W...
Self-Buckling of Pressurized Cylindrical Tubes
We investigate the buckling of hollow cylindrical tubes subject to their own weight and internal pressure, inspired by the columnar cells of the palisade mesophyll in dicotyledon leaves which resem...
Morten Opstrup Andersen, Nikolaj Tønner Osvald Olsen, Diksha Bhola, Aleca Borsuk, Craig Brodersen...
Measurement of Born Cross Sections for $e^+e^-\toΣ^-\barΣ^+$ at $\sqrt{s}=3.51-4.95$ GeV and Observation of $ψ(3770)\toΣ^-\barΣ^+$
Using $e^+e^-$ collision data corresponding to an integrated luminosity of 44 fb$^{-1}$ collected with the BESIII detector at the BEPCII collider, we report the first measurement of Born cross sect...
BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, C. S. Akondi, R. Alibert...
Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning
Recent work applies Large Language Models (LLMs) to source-code vulnerability detection, but most evaluations still rely on random train-test splits that ignore time and overestimate real-world per...
Xuhui Dou, Hayretdin Bahsi, Alejandro Guerra-Manzanares
OmniTrack: General Motion Tracking via Physics-Consistent Reference
Learning motion tracking from rich human motion data is a foundational task for achieving general control in humanoid robots, enabling them to perform diverse behaviors. However, discrepancies in m...
Yuhan Li, Peiyuan Zhi, Yunshen Wang, Tengyu Liu, Sixu Yan, Wenyu Liu, Xinggang Wang, Baoxiong Jia...
Efficient Tests for Testing in Two-way ANOVA under Heteroscedasticity
New tests are developed for two-way ANOVA models with heterogeneous error variances. The testing problems are considered for testing the significant interaction effects, simple effects, and treatme...
Anjana Mondal, Somesh Kumar
ReasonX: Declarative Reasoning on Explanations
Explaining opaque Machine Learning (ML) models has become an increasingly important challenge. However, current eXplanation in AI (XAI) methods suffer several shortcomings, including insufficient a...
Laura State, Salvatore Ruggieri, Franco Turini
GRAIL: Post-hoc Compensation by Linear Reconstruction for Compressed Networks
Structured deep model compression methods are hardware-friendly and substantially reduce memory and inference costs. However, under aggressive compression, the resulting accuracy degradation often ...
Wenwu Tang, Dong Wang, Lothar Thiele, Olga Saukh
Divide and Conquer: Accelerating Diffusion-Based Large Language Models via Adaptive Parallel Decoding
Diffusion-based large language models (dLLMs) have shown promising performance across various reasoning tasks, establishing themselves as an alternative to autoregressive large language models (LLM...
Xiangzhong Luo, Yilin An, Zhicheng Yu, Weichen Liu, Xu Yang
Fourier Angle Alignment for Oriented Object Detection in Remote Sensing
In remote sensing rotated object detection, mainstream methods suffer from two bottlenecks, directional incoherence at detector neck and task conflict at detecting head. Ulitising fourier rotation ...
Changyu Gu, Linwei Chen, Lin Gu, Ying Fu