Episode

04/04/25: Constrained Decoding for Code Language Models via Efficient Left and Right Quotienting of Context-Sensitive Grammars with Daniel Melcer

Podcast
Boston Computation Club
Published
Apr 5, 2025
Duration seconds
3513
Processing state
not_requested
Canonical source
https://podcasters.spotify.com/pod/show/bostoncc/episodes/040425-Constrained-Decoding-for-Code-Language-Models-via-Efficient-Left-and-Right-Quotienting-of-Context-Sensitive-Grammars-with-Daniel-Melcer-e3157l0
Audio
https://anchor.fm/s/5eee01ac/podcast/play/100883552/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2025-3-5%2F397878367-44100-2-eeec020aace74.mp3
JSON
/v1/public/podcasts/boston-computation-club-4031660/episodes/04-04-25-constrained-decoding-for-code-language-models-via-efficient-left-and-right-quotienting-of-context-sensitive-grammars-with-daniel-melcer
Markdown
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Summary

Today Daniel Melcer joined us to present Constrained Decoding for Code Language Models via Efficient Left and Right Quotienting of Context-Sensitive Grammars (https://arxiv.org/pdf/2402.17988). This is work he completed while at Amazon, and it's a really interesting project around how to constrain, guide, and check language models such that they generate valid code within a given context. We really appreciate that Daniel took the time to talk to us and hope you like the talk as much as we did!