4 papers
Stop Rewarding Hallucinated Steps: Faithfulness-Aware Step-Level Reinforcement Learning for Small Reasoning Models
Shuo Nie, Hexuan Deng, Chao Wang +6
As large language models become smaller and more efficient, small reasoning models (SRMs) are crucial for enabling chain-of-thought (CoT) reasoning in resource-constrained settings…
Learning to Watermark: A Selective Watermarking Framework for Large Language Models via Multi-Objective Optimization
Chenrui Wang, Junyi Shu, Billy Chiu +4
The rapid development of LLMs has raised concerns about their potential misuse, leading to various watermarking schemes that typically offer high detectability. However, existing w…
CDT: A Comprehensive Capability Framework for Large Language Models Across Cognition, Domain, and Task
Haosi Mo, Xinyu Ma, Xuebo Liu +4
Recent advances in Large Language Models (LLMs) have significantly enhanced their capabilities, highlighting the need for comprehensive evaluation frameworks that extend beyond tas…
Function-to-Style Guidance of LLMs for Code Translation
Longhui Zhang, Bin Wang, Jiahao Wang +7
Large language models (LLMs) have made significant strides in code translation tasks. However, ensuring both the correctness and readability of translated code remains a challenge,…