[Submitted on 17 Apr 2025 (v1), last revised 2 Jul 2025 (this version, v2)] View a PDF of the paper titled Query Complexity of Classical and Quantum Channel Discrimination, by Theshani Nuradha and 1 other authors View PDF HTML (experimental) Abstract:Quantum channel discrimination has been studied from an information-theoretic perspective, wherein one is interested in […]

[Submitted on 2 Jul 2025] View a PDF of the paper titled Adaptability of ASR Models on Low-Resource Language: A Comparative Study of Whisper and Wav2Vec-BERT on Bangla, by Md Sazzadul Islam Ridoy and 2 other authors View PDF HTML (experimental) Abstract:In recent years, neural models trained on large multilingual text and speech datasets have

arXiv:2507.00435v1 Announce Type: cross Abstract: We present RoboEval, a simulation benchmark and structured evaluation framework designed to reveal the limitations of current bimanual manipulation policies. While prior benchmarks report only binary task success, we show that such metrics often conceal critical weaknesses in policy behavior — such as poor coordination, slipping during grasping, or asymmetric

arXiv:2507.01770v1 Announce Type: cross Abstract: This paper introduces a GPU-based complete search method to enclose the global minimum of a nonlinear function subject to simple bounds on the variables. Using interval analysis, coupled with the computational power and architecture of GPU, the method iteratively rules out the regions in the search domain where the global

[Submitted on 13 May 2024 (v1), last revised 1 Jul 2025 (this version, v2)] Authors:Antoine Bellemare-Pepin (1 and 2), François Lespinasse (3), Philipp Thölke (1), Yann Harel (1), Kory Mathewson (4), Jay A. Olson (5), Yoshua Bengio (4 and 6), Karim Jerbi (1, 4 and 7) ((1) CoCo Lab, Psychology department, Université de Montréal, Montreal,

[Submitted on 1 Jul 2025 (v1), last revised 2 Jul 2025 (this version, v2)] View a PDF of the paper titled Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess, by Dongyoon Hwang and 4 other authors View PDF HTML (experimental) Abstract:While reinforcement learning (RL) for large language models (LLMs) has shown

[Submitted on 24 Jun 2025 (v1), last revised 1 Jul 2025 (this version, v2)] View a PDF of the paper titled AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration, by Xiangbo Gao and 8 other authors View PDF HTML (experimental) Abstract:While multi-vehicular collaborative driving demonstrates clear advantages over single-vehicle autonomy, traditional infrastructure-based V2X systems remain constrained by substantial

arXiv:2507.01597v1 Announce Type: cross Abstract: Temporal Knowledge Graph (TKG) is an efficient method for describing the dynamic development of facts along a timeline. Most research on TKG reasoning (TKGR) focuses on modelling the repetition of global facts and designing patterns of local historical facts. However, they face two significant challenges: inadequate modeling of the event