3 citations · 3 across the 9 of their papers we have counts for
10 papers
Ideation Arena: Evaluating LLM Generated Research Ideas with Battle-style Human Expert Assessment
Zhiyu Chen, Keyu Zhao, Jigao Fu +8
Evaluating research ideas generated by LLMs is difficult because their scientific value cannot be fully determined by objective criteria, and no single reference answer specifies w…
Agentic-Ideation: Sample Efficient Agentic Trajectories Synthesis for Scientific Ideation Agents
Keyu Zhao, Lingyan Kong, Fengli Xu +1
Ideation plays a pivotal role in scientific discovery. Recent LLM, especially AI Scientist systems, show promising potential for automated ideation. However, existing approaches pr…
OptSkills: Learning Generalizable Optimization Skills from Problem Archetypes via Cluster-Based Distillation
Haochen Yang, Ke Zhao, Mengyuan Ma +3
Leveraging Large Language Models (LLMs) to automatically formulate and solve optimization problems from natural language has emerged as an efficient paradigm for automated optimiza…
HybridQuestion: Human-AI Collaboration for Identifying High-Impact Research Questions
Keyu Zhao, Fengli Xu, Yong Li +1
The "AI Scientist" paradigm is transforming scientific research by automating key stages of the research process, from idea generation to scholarly writing. This shift is expected…
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Chenyang Shao, Dehao Huang, Yu Li +18
With the rapid development of Large Language Models (LLMs), AI agents have demonstrated increasing proficiency in scientific tasks, ranging from hypothesis generation and experimen…
Deep Ideation: Designing LLM Agents to Generate Novel Research Ideas on Scientific Concept Network
Keyu Zhao, Weiquan Lin, Qirui Zheng +2
Novel research ideas play a critical role in advancing scientific inquiries. Recent advancements in Large Language Models (LLMs) have demonstrated their potential to generate novel…
AI Agent Behavioral Science
Lin Chen, Yunke Zhang, Jie Feng +13
Recent advances in large language models (LLMs) have enabled the development of AI agents that exhibit increasingly human-like behaviors, including planning, adaptation, and social…
Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation
Keyu Zhao, Fengli Xu, Yong Li
Driven by advances in Large Language Models (LLMs), integrating them into recommendation tasks has gained interest due to their strong semantic understanding and prompt flexibility…
AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms
Yuwei Yan, Yu Shang, Qingbin Zeng +9
The AgentSociety Challenge is the first competition in the Web Conference that aims to explore the potential of Large Language Model (LLM) agents in modeling user behavior and enha…
AgentSquare: Automatic LLM Agent Search in Modular Design Space
Yu Shang, Yu Li, Keyu Zhao +4
Recent advancements in Large Language Models (LLMs) have led to a rapid growth of agentic systems capable of handling a wide range of complex tasks. However, current research large…