5 papers
IceBreaker for Conversational Agents: Breaking the First-Message Barrier with Personalized Starters
Hongwei Zheng, Weiqi Wu, Zhengjia Wang +6
Conversational agents, such as ChatGPT and Doubao, have become essential daily assistants for billions of users. To further enhance engagement, these systems are evolving from pass…
PLANET: A Collection of Benchmarks for Evaluating LLMs' Planning Capabilities
Haoming Li, Zhaoliang Chen, Jonathan Zhang +1
Planning is central to agents and agentic AI. The ability to plan, e.g., creating travel itineraries within a budget, holds immense potential in both scientific and commercial cont…
Systematic Analysis of LLM Contributions to Planning: Solver, Verifier, Heuristic
Haoming Li, Zhaoliang Chen, Songyuan Liu +2
In this work, we provide a systematic analysis of how large language models (LLMs) contribute to solving planning problems. In particular, we examine how LLMs perform when they are…
LASP: Surveying the State-of-the-Art in Large Language Model-Assisted AI Planning
Haoming Li, Zhaoliang Chen, Jonathan Zhang +1
Effective planning is essential for the success of any task, from organizing a vacation to routing autonomous vehicles and developing corporate strategies. It involves setting goal…
Rescue: Ranking LLM Responses with Partial Ordering to Improve Response Generation
Yikun Wang, Rui Zheng, Haoming Li +3
Customizing LLMs for a specific task involves separating high-quality responses from lower-quality ones. This skill can be developed using supervised fine-tuning with extensive hum…