7 citations · 7 across the 7 of their papers we have counts for
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cs.AI2026
Language-based Trial and Error Falls Behind in the Era of Experience
Haoyu Wang, Guozheng Ma, Shugang Cui +7
While Large Language Models (LLMs) excel in language-based agentic tasks, their applicability to unseen, nonlinguistic environments (e.g., symbolic or spatial tasks) remains limite…
cs.AI2024
QPO: Query-dependent Prompt Optimization via Multi-Loop Offline Reinforcement Learning
Yilun Kong, Hangyu Mao, Qi Zhao +7
Prompt engineering has demonstrated remarkable success in enhancing the performance of large language models (LLMs) across diverse tasks. However, most existing prompt optimization…
cs.AI2023★ 7 cited
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems
Yilun Kong, Jingqing Ruan, Yihong Chen +9
Large Language Models (LLMs) have demonstrated proficiency in addressing tasks that necessitate a combination of task planning and the usage of external tools that require a blend…