activity
20222026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 621 across the 39 of their papers we have counts for

collaborators
Showing cs.AIShow all

5 papers · 1 filter

cs.AI2026

Same Operation, Different Permission: Evaluating Whether Guardrails Honor Authorization

Huihao Jing, Shaojin Chen, Wenbin Hu +5

As language-model agents write code, move money and change records on behalf of users, deciding whether an action is authorized has become a central safety problem. Guardrails are…

cs.AI2026

SkillScriptBench: Benchmarking Self-Evolution of Executable Agent Skill Packages Beyond Markdown

Yuxuan Liu, Haoran Li, Yuhao Zhang +10

Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing errors without breaking correct b…

cs.AI2026

Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions

Huihao Jing, Wenbin Hu, Shaojin Chen +10

The capability of LLM agents to function as the ``brain'' of a system fundamentally expands the scope of analysis beyond a standalone model. Consequently, safety is no longer only…

cs.AI2026

SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision

Yuxuan Liu, Zhaochen Su, Lingyun Xie +11

Agent skills are procedural artifacts that enable LLM agents to execute workflows, verify constraints, and recover from failures. Existing self-evolving methods refine skills using…

cs.AI2025

MASLegalBench: Benchmarking Multi-Agent Systems in Deductive Legal Reasoning

Huihao Jing, Wenbin Hu, Hongyu Luo +4

Multi-agent systems (MAS), leveraging the remarkable capabilities of Large Language Models (LLMs), show great potential in addressing complex tasks. In this context, integrating MA…