11 papers
Tree-based Credit Assignment for Multi-Agent Memory System
Marina Mao, Alexandr Liu, Pengbo Li +3
Memory systems are widely adopted to enhance LLMs for long-horizon tasks, and are commonly organized as multi-agent pipelines with memory building, summarizing, and retrieval agent…
Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
Yuanqi Du, Botao Yu, Tianyu Liu +25
There has been unprecedented interest in developing agents that expand the boundary of scientific discovery, primarily by optimizing quantitative objective functions specified by s…
Discovery and Reinforcement of Tool-Integrated Reasoning Chains via Rollout Trees
Kun Li, Zenan Xu, Junan Li +4
Tool-Integrated Reasoning has emerged as a key paradigm to augment Large Language Models (LLMs) with computational capabilities, yet integrating tool-use into long Chain-of-Thought…
Segmental Advantage Estimation: Enhancing PPO for Long-Context LLM Training
Xue Gong, Qi Yi, Ziyuan Nan +8
Training Large Language Models (LLMs) for reasoning tasks is increasingly driven by Reinforcement Learning with Verifiable Rewards (RLVR), where Proximal Policy Optimization (PPO)…
ConMax: Confidence-Maximizing Compression for Efficient Chain-of-Thought Reasoning
Minda Hu, Zexuan Qiu, Zenan Xu +3
Recent breakthroughs in Large Reasoning Models (LRMs) have demonstrated that extensive Chain-of-Thought (CoT) generation is critical for enabling intricate cognitive behaviors, suc…
ATPO: Agentic Turn-based Policy Optimization via Tree Search
Zefang Zong, Dingwei Chen, Yang Li +6
LLM agents have emerged as powerful systems for tackling multi-turn tasks by interleaving internal reasoning and external tool interactions. Agentic Reinforcement Learning has rece…