2 citations · 4 across the 6 of their papers we have counts for
7 papers
ACLArena: Agent Continue Learning in Multi-stage Post-training
Haixin Wang, Xiaoxuan Wang, Junkai Zhang +9
Building general-purpose agents for industrial deployment requires integrating multiple capabilities, each typically acquired at a distinct stage of training. Yet there is currentl…
Structure-Aware RAG: Structured Retrieval Augmented Generation from Noisy Data for Conversational Agents
Kaiqiao Han, LuAn Tang, Renliang Sun +6
Large Language Models (LLMs) have been widely adopted in conversational applications. However, their reliance on parametric knowledge limits reliability in real-world scenarios tha…
FitText: Evolving Agent Tool Ecologies via Memetic Retrieval
Kyle Zheng, Han Zhang, Renliang Sun +2
Efficient reasoning is not only a matter of shortening an answer trace; for tool-using agents, it also depends on whether the agent is reasoning over the right action space. As API…
ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning
Xiaoxuan Wang, Han Zhang, Haixin Wang +11
Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interactive tasks. Despite encouraging ea…
Stop When Enough: Adaptive Early-Stopping for Chain-of-Thought Reasoning
Renliang Sun, Wei Cheng, Dawei Li +2
Chain-of-Thought (CoT) reasoning has driven recent gains of large language models (LLMs) on reasoning-intensive tasks by externalizing intermediate steps. However, excessive or red…
Protein Large Language Models: A Comprehensive Survey
Yijia Xiao, Wanjia Zhao, Junkai Zhang +12
Protein-specific large language models (Protein LLMs) are revolutionizing protein science by enabling more efficient protein structure prediction, function annotation, and design.…
Preference Leakage: A Contamination Problem in LLM-as-a-judge
Dawei Li, Renliang Sun, Yue Huang +6
Large Language Models (LLMs) as judges and LLM-based data synthesis have emerged as two fundamental LLM-driven data annotation methods in model development. While their combination…