3 papers
cs.CL2025
Thinker: Learning to Think Fast and Slow
Stephen Chung, Wenyu Du, Jie Fu
Recent studies show that the reasoning capabilities of Large Language Models (LLMs) can be improved by applying Reinforcement Learning (RL) to question-answering (QA) tasks in area…
cs.CL2025
Finite State Automata Inside Transformers with Chain-of-Thought: A Mechanistic Study on State Tracking
Yifan Zhang, Wenyu Du, Dongming Jin +2
Chain-of-thought (CoT) significantly enhances the performance of large language models (LLMs) across a wide range of tasks, and prior research shows that CoT can theoretically incr…
cs.CL2025
Learning from Failures in Multi-Attempt Reinforcement Learning
Stephen Chung, Wenyu Du, Jie Fu
Recent advancements in reinforcement learning (RL) for large language models (LLMs), exemplified by DeepSeek R1, have shown that even a simple question-answering task can substanti…