1 citations · 2 across the 7 of their papers we have counts for
10 papers
Live-Evo: Online Evolution of Agentic Memory from Continuous Feedback
Yaolun Zhang, Yiran Wu, Yijiong Yu +2
Large language model (LLM) agents are increasingly equipped with memory, which are stored experience and reusable guidance that can improve task-solving performance. Recent \emph{s…
Design-Based Bandits Under Network Interference: Trade-Off Between Regret and Statistical Inference
Zichen Wang, Haoyang Hong, Chuanhao Li +3
In multi-armed bandits with network interference (MABNI), the action taken by one node can influence the rewards of others, creating complex interdependence. While existing researc…
The Ranking Blind Spot: Decision Hijacking in LLM-based Text Ranking
Yaoyao Qian, Yifan Zeng, Yuchao Jiang +2
Large Language Models (LLMs) have demonstrated strong performance in information retrieval tasks like passage ranking. Our research examines how instruction-following capabilities…
A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence
Huan-ang Gao, Jiayi Geng, Wenyue Hua +24
Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse tasks but remain fundamentally static, unable to adapt their internal parameters to novel task…
SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement
Chelsi Jain, Yiran Wu, Yifan Zeng +5
Document Visual Question Answering (DocVQA) is a practical yet challenging task, which is to ask questions based on documents while referring to multiple pages and different modali…
Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems
Shaokun Zhang, Ming Yin, Jieyu Zhang +8
Failure attribution in LLM multi-agent systems-identifying the agent and step responsible for task failures-provides crucial clues for systems debugging but remains underexplored a…