8 citations · 10 across the 9 of their papers we have counts for
Showing 2026 · cs.AIShow all
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cs.AI2026
ACM: Agentic Context Management for Long Horizon Tasks
Xiaochuan Li, Ryan Ming, Meng Chu +3
Agentic tasks are inherently long-horizon and multi-turn, constantly accumulating context through interactions with the environment. Existing context compression methods inevitably…
cs.AI2026
Closed-loop Auto Research for Molecular Property Prediction: Discovering and Certifying Generalizable Improvements
Jingjie Ning, Xiaochuan Li, Ji Zeng +2
Closed-loop Auto Research extends automated machine learning from fixed-dataset fitting to changing the research workflow, with language-model agents editing representations and mo…
cs.AI2026★ 2 cited
Evaluating Test-Time Scaling of General LLM Agents
Xiaochuan Li, Ryan Ming, Pranav Setlur +6
LLM agents are increasingly expected to operate as general-purpose systems that resolve real-world user requests, yet their dynamic scaling behavior in realistic environments remai…