4 citations · 12 across the 9 of their papers we have counts for
7 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…
Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization
Shiping Gao, Hongzhan Chen, Xiaojun Quan +2
Process reward models (PRMs) provide fine-grained supervision for reasoning, but reliable PRMs often require step annotations or heavy verification pipelines, making them costly to…
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…
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…
AD-KD: Attribution-Driven Knowledge Distillation for Language Model Compression
Siyue Wu, Hongzhan Chen, Xiaojun Quan +2
Knowledge distillation has attracted a great deal of interest recently to compress pre-trained language models. However, existing knowledge distillation methods suffer from two lim…