3 citations · 3 across the 4 of their papers we have counts for
5 papers
Mara Chain: Rethinking Failure as a Stepping Stone for AI System Auto-Evolution
Yubin Lyu, Fu Li, Jiawei Fei +3
Optimizing deployed AI systems increasingly amounts to editing prompts, skills, harnesses, and code rather than model weights. Existing approaches commonly optimize these artifacts…
From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning
Beining Wu, Fuyou Mao, Jiong Lin +7
Generative engines (GEs) are reshaping information access by replacing ranked links with citation-grounded answers, yet current Generative Engine Optimization (GEO) methods optimiz…
ChainRec: An Agentic Recommender Learning to Route Tool Chains for Diverse and Evolving Interests
Fuchun Li, Qian Li, Xingyu Gao +7
Large language models (LLMs) are increasingly integrated into recommender systems, motivating recent interest in agentic and reasoning-based recommendation. However, most existing…
BeSimulator: A Large Language Model Powered Text-based Behavior Simulator
Jianan Wang, Bin Li, Jingtao Qi +3
Traditional robot simulators focus on physical process modeling and realistic rendering, often suffering from high computational costs, inefficiencies, and limited adaptability. To…
A Study on Training and Developing Large Language Models for Behavior Tree Generation
Fu Li, Xueying Wang, Bin Li +3
This paper presents an innovative exploration of the application potential of large language models (LLM) in addressing the challenging task of automatically generating behavior tr…