Planning in the LLM Era: Building for Reliability and Efficiency
Growing attention to intelligent agents has put a spotlight on one of their central capabilities: planning. Early attempts to leverage large language models (LLMs) for planning relied on single-shot plan generation, followed by hybrid approaches that coupled LLMs with limited external search. These methods, unsound and incomplete by their very nature, often require substantial resources without yielding better solutions on unseen problems. As the limitations of LLMs become clearer, recent work has shifted toward using them at solution construction time -- generating symbolic solvers for a family of problems that can be verified and then used efficiently at inference time. This trend refle...
| Authors | Michael Katz, Harsha Kokel, Kavitha Srinivas et al. |
|---|---|
| Primary category | cs.AI |
| Published | 21 May 2026 |
| Last updated at source | 21 May 2026 |
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