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arXiv:2604.02525v1 Announce Type: new Abstract: Low-precision training (LPT) commonly employs Hadamard transforms to suppress outliers and mitigate quantization error in large language models (LLMs). However, …
arXiv:2604.02348v1 Announce Type: new Abstract: Reinforcement learning (RL) has produced spectacular results in games, robotics, and continuous control. Yet, despite these successes, learned policies often …
arXiv:2604.03071v1 Announce Type: new Abstract: We present a case study where an automatic AI system formalizes a textbook with more than 500 pages of graduate-level …
arXiv:2604.02967v1 Announce Type: new Abstract: Recent Large Reasoning Models (LRMs) like DeepSeek-R1 have demonstrated remarkable success in complex reasoning tasks, exhibiting human-like patterns in exploring …
arXiv:2604.02430v1 Announce Type: new Abstract: In this work, we present a novel machine learning framework called Self-Directed Task Identification (SDTI), which enables models to autonomously …
arXiv:2604.02512v1 Announce Type: new Abstract: Large language models (LLMs) increasingly exhibit human-like patterns of pragmatic and social reasoning. This paper addresses two related questions: do …
arXiv:2604.02830v1 Announce Type: new Abstract: Detecting whether a model's internal knowledge is sufficient to correctly answer a given question is a fundamental challenge in deploying …
arXiv:2604.03004v1 Announce Type: new Abstract: While deep reasoning with long chain-of-thought has dramatically improved large language models in verifiable domains like mathematics, its effectiveness for …
arXiv:2604.02770v1 Announce Type: new Abstract: In large language model (LLM)-driven multi-agent systems, disobey role specification (failure to adhere to the defined responsibilities and constraints of …
arXiv:2604.02660v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly power decision-making systems across critical domains, understanding and mitigating their biases becomes essential for …
arXiv:2604.03216v1 Announce Type: new Abstract: Large language models (LLMs) often produce confident but incorrect answers in settings where abstention would be safer. Standard evaluation protocols, …
arXiv:2604.02451v1 Announce Type: new Abstract: Modeling coherence in text has been a task that has excited NLP researchers since a long time. It has applications …