AI RESEARCH
Constraints-of-Thought: A Framework for Constrained Reasoning in Language-Model-Guided Search
arXiv CS.LG
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ArXi:2510.08992v2 Announce Type: replace While researchers have made significant progress in enabling large language models (LLMs) to perform multi-step planning, LLMs struggle to ensure that those plans align with high-level user intent and satisfy symbolic constraints, especially in complex, multi-step domains. Existing reasoning approaches such as Chain-of-Thought (CoT), Tree-of-Thought (ToT), and verifier-augmented methods, expand the search space but often yield infeasible actions or hallucinated steps.