Fei Liu

PlanGenLLMs: A Modern Survey of LLM Planning Capabilities LLMs have immense potential for generating plans, transforming an initial world state into a desired goal state. A large body of research has explored the use of LLMs for various planning tasks, from ...

That makes it difficult to compare systems across domains, or figure out which one's best for a new planning problem.

That's where our paper comes in: We offer a comprehensive overview of LLM planning agents, highlighting gaps, challenges, and what's next.

Check it out 👉 arxiv.org/abs/2502.11221

🧠 Planning is a core aspect of both human and artificial intelligence.

LLMs/agents have been used in various planning tasks, from navigating websites and planning trips to querying databases, but most benchmarks are narrow and task-specific.

🏆 Thrilled that our paper #PlanGenLLMs (arxiv.org/abs/2502.11221) won the SAC Award at #ACL2025!!

Couldn't have done it without the amazing team: Hui Wei, Zihao Zhang, Shenghua He, Tian Xia, and Shijia Pan. So thankful and beyond proud! 💖 #ACL2025NLP #NLProc

Happy to share our paper got selected as an Oral Presentation at #ACL2025!

Out of 8,000+ submissions and 3,000+ accepted papers, only 245 were chosen for oral (<3%)!

📄 Paper: arxiv.org/abs/2502.11221
💻 Resource: github.com/wll199566/Aw...

Autonomous agents are powerful, but without guardrails, they drift into inefficiency.

We view 'cost' as a form of guardrail and use Monte Carlo Tree Search with explicit cost-awareness to guide LLM-based planning.

Link: arxiv.org/pdf/2505.14656