mcyc

  - https://github.com/dottxt-ai/outlines

  - https://github.com/guidance-ai/guidance

  - https://github.com/mlc-ai/xgrammar

  - This one has a lot of cool technical aspects that make it an interesting project

  - By the outlines authors, probably the first real LLM constrained generation paper

  - https://arxiv.org/abs/2307.09702

  - A much more technical paper about constrained generation and implementation

  - https://arxiv.org/abs/2407.08103

  - A bit of self-promotion. We show where constrained generation can go wrong and discuss some techniques for the practitioner

  - https://openreview.net/pdf?id=DFybOGeGDS

  - Discusses adhering to the canonical tokenization (i.e., not just the constraint, but also what would be produced by the tokenizer)

  - https://vivien000.github.io/blog/journal/llm-decoding-with-regex-constraints.html

  - Also from the outlines team

  - This is about skipping inference during constrained generation if you know there is only one valid token (common in the canonical tokenization setting)

  - https://blog.dottxt.ai/coalescence.html