4 citations · 10 across the 10 of their papers we have counts for
8 papers · 1 filter
Cross-Domain Hybrid OPD for Generalizable Search Agents
Hongzhan Chen, Xiaoyu Liu, Dengming Zhang +11
Recent advances in Reinforcement Learning (RL) have substantially improved the capabilities of autonomous search agents, enabling sophisticated planning, and iterative retrieval ov…
SPELL: Self-Play Reinforcement Learning for Evolving Long-Context Language Models
Ziyi Yang, Weizhou Shen, Chenliang Li +5
Progress in long-context reasoning for large language models (LLMs) has lagged behind other recent advances. This gap arises not only from the intrinsic difficulty of processing lo…
Discriminative Policy Optimization for Token-Level Reward Models
Hongzhan Chen, Tao Yang, Shiping Gao +4
Process reward models (PRMs) provide more nuanced supervision compared to outcome reward models (ORMs) for optimizing policy models, positioning them as a promising approach to enh…
ProFuser: Progressive Fusion of Large Language Models
Tianyuan Shi, Fanqi Wan, Canbin Huang +6
While fusing the capacities and advantages of various large language models offers a pathway to construct more powerful and versatile models, a fundamental challenge is to properly…
Cool-Fusion: Fuse Large Language Models without Training
Cong Liu, Xiaojun Quan, Yan Pan +3
We focus on the problem of fusing two or more heterogeneous large language models (LLMs) to leverage their complementary strengths. One of the challenges of model fusion is high co…
SocialBench: Sociality Evaluation of Role-Playing Conversational Agents
Hongzhan Chen, Hehong Chen, Ming Yan +8
Large language models (LLMs) have advanced the development of various AI conversational agents, including role-playing conversational agents that mimic diverse characters and human…
Knowledge Distillation of Black-Box Large Language Models
Hongzhan Chen, Ruijun Chen, Yuqi Yi +4
Given the exceptional performance of proprietary large language models (LLMs) like GPT-4, recent research has increasingly focused on boosting the capabilities of smaller models th…
MCC-KD: Multi-CoT Consistent Knowledge Distillation
Hongzhan Chen, Siyue Wu, Xiaojun Quan +3
Large language models (LLMs) have showcased remarkable capabilities in complex reasoning through chain of thought (CoT) prompting. Recently, there has been a growing interest in tr…