2 citations · 2 across the 5 of their papers we have counts for
6 papers
SE-Bench: Benchmarking Self-Evolution with Knowledge Internalization
Jiarui Yuan, Tailin Jin, Weize Chen +1
True self-evolution requires agents to act as lifelong learners that internalize novel experiences to solve future problems. However, rigorously measuring this foundational capabil…
CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning
Ran Li, Zeyuan Liu, Yinghao Chen +8
Large Language Models (LLMs) have demonstrated strong potential in complex reasoning, yet their progress remains fundamentally constrained by reliance on massive high-quality human…
The Overthinker's DIET: Cutting Token Calories with DIfficulty-AwarE Training
Weize Chen, Jiarui Yuan, Tailin Jin +4
Recent large language models (LLMs) exhibit impressive reasoning but often over-think, generating excessively long responses that hinder efficiency. We introduce DIET ( DIfficulty-…
Process Reinforcement through Implicit Rewards
Ganqu Cui, Lifan Yuan, Zefan Wang +22
Dense process rewards have proven a more effective alternative to the sparse outcome-level rewards in the inference-time scaling of large language models (LLMs), particularly in ta…
Optima: Optimizing Effectiveness and Efficiency for LLM-Based Multi-Agent System
Weize Chen, Jiarui Yuan, Chen Qian +3
Large Language Model (LLM) based multi-agent systems (MAS) show remarkable potential in collaborative problem-solving, yet they still face critical challenges: low communication ef…
Beyond Natural Language: LLMs Leveraging Alternative Formats for Enhanced Reasoning and Communication
Weize Chen, Chenfei Yuan, Jiarui Yuan +6
Natural language (NL) has long been the predominant format for human cognition and communication, and by extension, has been similarly pivotal in the development and application of…