7 citations · 19 across the 15 of their papers we have counts for
4 papers · 1 filter
Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming
Yilun Hao, Yang Zhang, Chuchu Fan
While large language models (LLMs) have recently demonstrated strong potential in solving planning problems, there is a trade-off between flexibility and complexity. LLMs, as zero-…
Steering Large Language Models between Code Execution and Textual Reasoning
Yongchao Chen, Harsh Jhamtani, Srinagesh Sharma +2
While a lot of recent research focuses on enhancing the textual reasoning capabilities of Large Language Models (LLMs) by optimizing the multi-agent framework or reasoning chains,…
Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools
Yilun Hao, Yongchao Chen, Yang Zhang +1
Large Language Models (LLMs) struggle to directly generate correct plans for complex multi-constraint planning problems, even with self-verification and self-critique. For example,…
PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Heuristic-based Sampling
Yongchao Chen, Jacob Arkin, Yilun Hao +3
Prompt optimization aims to find the best prompt to a large language model (LLM) for a given task. LLMs have been successfully used to help find and improve prompt candidates for s…