4 papers
SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models
Weijiang Lv, Yaoxuan Feng, Xiaobo Xia +4
Chain-of-Thought reasoning is widely used to improve the interpretability of multimodal large language models (MLLMs), yet the faithfulness of the generated reasoning traces remain…
Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning
Jiayu Wang, Yifei Ming, Zixuan Ke +4
Reinforcement learning (RL) has become the dominant paradigm for improving the performance of language models on complex reasoning tasks. Despite the substantial empirical gains de…
COSMOS: Predictable and Cost-Effective Adaptation of LLMs
Jiayu Wang, Aws Albarghouthi, Frederic Sala
Large language models (LLMs) achieve remarkable performance across numerous tasks by using a diverse array of adaptation strategies. However, optimally selecting a model and adapta…
The Widespread Adoption of Large Language Model-Assisted Writing Across Society
Weixin Liang, Yaohui Zhang, Mihai Codreanu +3
The recent advances in large language models (LLMs) attracted significant public and policymaker interest in its adoption patterns. In this paper, we systematically analyze LLM-ass…