When will LLMs be able to output in a fixed format (JSON?)
This article explores methods for enabling LLMs to output fixed formats (such as JSON), including the universal prompt approach, post-inference processing solutions (regular expressions), and in-inference processing solutions (dynamic constrained decoding). It analyzes the advantages, disadvantages, and applicable scenarios of each method, and points out the limitations of current research.
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