9 papers
OnePred: Next-Query Prediction via Recursive Intent Memory in Multi-Turn Conversations
Jiangwang Chen, Bowen Zhang, Zixin Song +4
Although large language model (LLM) conversational systems process millions of multi-turn dialogues daily, they remain fundamentally reactive: they respond only after the user type…
Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents
Jiazheng Kang, Bowen Zhang, Zixin Song +4
ReAct-style agents for search-intensive, multi-step reasoning tasks rely largely on their own internal judgment to decide what evidence to seek, which reasoning or action step to t…
KCoEvo: A Knowledge Graph Augmented Framework for Evolutionary Code Generation
Jiazhen Kang, Yuchen Lu, Chen Jiang +6
Code evolution is inevitable in modern software development. Changes to third-party APIs frequently break existing code and complicate maintenance, posing practical challenges for…
LFPO: Likelihood-Free Policy Optimization for Masked Diffusion Models
Chenxing Wei, Jiazhen Kang, Hong Wang +8
Reinforcement Learning with Verifiable Rewards (RLVR) has achieved remarkable success in improving autoregressive models, especially in domains requiring correctness like mathemati…
Self-Evolving LLMs via Continual Instruction Tuning
Jiazheng Kang, Le Huang, Cheng Hou +3
In real-world industrial settings, large language models (LLMs) must learn continually to keep pace with diverse and evolving tasks, requiring self-evolution to refine knowledge un…
OneEval: Benchmarking LLM Knowledge-intensive Reasoning over Diverse Knowledge Bases
Yongrui Chen, Zhiqiang Liu, Jing Yu +21
Large Language Models (LLMs) have demonstrated substantial progress on reasoning tasks involving unstructured text, yet their capabilities significantly deteriorate when reasoning…