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20242026
most citedAdapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges

18 citations · 19 across the 14 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents

Qingyao Li, Wenxiang Jiao, Shuai Shao +6

Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, while public libraries now hold thousands of them. Which skill to…

cs.AI2026

Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories

Shuai Shao, Kangning Zhang, Qingyao Li +7

Agents built around large language models continually accumulate interaction trajectories during deployment, yet their behavior typically remains fixed. Beyond updating model weigh…

cs.AI2026

MMSkills: Towards Multimodal Skills for General Visual Agents

Kangning Zhang, Shuai Shao, Qingyao Li +8

Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as textual prompts, executable co…

cs.AI2026

Plan-MCTS: Plan Exploration for Action Exploitation in Web Navigation

Weiming Zhang, Jihong Wang, Jiamu Zhou +9

Large Language Models (LLMs) have empowered autonomous agents to handle complex web navigation tasks. While recent studies integrate tree search to enhance long-horizon reasoning,…

cs.AI2024★ 18 cited

Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges

Qingyao Li, Lingyue Fu, Weiming Zhang +6

Online education platforms, leveraging the internet to distribute education resources, seek to provide convenient education but often fall short in real-time communication with stu…