55 citations · 72 across the 38 of their papers we have counts for
9 papers · 1 filter
Failure Recovery via Belief Updates and World Modeling for Long-Horizon Agents
Xiyang Wu, Zhichao Liu, Shengxin zhang +4
Long-horizon agents often struggle to recover from failures whose causes lie several steps earlier, beyond what local reflection or backtracking can resolve. We introduce BELIEFWEA…
Superminds Test: Actively Evaluating Collective Intelligence of Agent Society via Probing Agents
Xirui Li, Ming Li, Yunze Xiao +4
Collective intelligence refers to the ability of a group to achieve outcomes beyond what any individual member can accomplish alone. As large language model agents scale to populat…
ClawEnvKit: Automatic Environment Generation for Claw-Like Agents
Xirui Li, Ming Li, Ion Stoica +2
Constructing environments for training and evaluating claw-like agents remains a manual, human-intensive process that does not scale. We argue that what is needed is not just a dat…
Swift-SVD: Theoretical Optimality Meets Practical Efficiency in Low-Rank LLM Compression
Ruoling Qi, Yirui Liu, Xuaner Wu +6
The deployment of Large Language Models is constrained by the memory and bandwidth demands of static weights and dynamic Key-Value cache. SVD-based compression provides a hardware-…
When AI Navigates the Fog of War
Ming Li, Xirui Li, Tianyi Zhou
Can AI reason about a war before its trajectory becomes historically obvious? Analyzing this capability is difficult because retrospective geopolitical prediction is heavily confou…
Does Socialization Emerge in AI Agent Society? A Case Study of Moltbook
Ming Li, Xirui Li, Tianyi Zhou
As large language model agents increasingly populate networked environments, a fundamental question arises: do artificial intelligence (AI) agent societies undergo convergence dyna…
What does RL improve for Visual Reasoning? A Frankenstein-Style Analysis
Xirui Li, Ming Li, Tianyi Zhou
Reinforcement learning (RL) with verifiable rewards has become a standard post-training stage for boosting visual reasoning in vision-language models, yet it remains unclear what c…
Towards Valid Student Simulation with Large Language Models
Zhihao Yuan, Yunze Xiao, Ming Li +4
This paper presents a conceptual and methodological framework for large language model (LLM) based student simulation in educational settings. The authors identify a core failure m…
Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry
Zhuochun Li, Yong Zhang, Ming Li +8
Large language models (LLMs) are widely used as reference-free evaluators via prompting, but this "LLM-as-a-Judge" paradigm is costly, opaque, and sensitive to prompt design. In th…