Thinking Before Constraining: A Unified Decoding Framework for Large Language Models 事件

Thinking Before Constraining: A Unified Decoding Framework for Large Language Models arXiv:2601.07525v2 Announce Type: replace Abstract: Natural generation allows Large Language Models (LLMs) to produce free-form responses with rich reasoning, yet the lack of structure makes outputs difficult to verify. Conversely, constrained decoding ensures standardized formats but can inadvertently restrict reasoning capabilities by imposing constraints too early in the generation process. We propose a hybr