repoGitHubTrust 82 · PrimaryPublished yesterdayLive · yesterday
ndcorder/outputguard
Validate, repair, and retry LLM structured outputs. 13 repair strategies for common JSON malformations, JSON Schema validation, and retry-with-feedback prompts.
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- PossiblePossibly related (embedding) · 54%A cheap trick for reliable structured output: feed the validation error back into the retry →
- PossiblePossibly related (embedding) · 52%Form, Not Content? A Preregistered, Placebo-Controlled Evaluation of Learned Error-Conditioned Self-Repair Through Prompts and Weights in Frozen Small Code Models →
- PossiblePossibly related (embedding) · 51%Structured output reliability with LLMs — 3-month production learnings →
- PossiblePossibly related (embedding) · 47%Falsification, Not Exposure: An Internally Preregistered Placebo-Controlled Decomposition of Self-Repair Feedback in Frozen Small Code Models →
- PossiblePossibly related (embedding) · 45%Mechanism-Driven Monitors for Preemptive Detection of LLM Training Instability →
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Implements
paperForm, Not Content? A Preregistered, Placebo-Controlled Evaluation of Learned Error-Conditioned Self-Repair Through Prompts and Weights in Frozen Small Code ModelspaperFalsification, Not Exposure: An Internally Preregistered Placebo-Controlled Decomposition of Self-Repair Feedback in Frozen Small Code ModelspaperMechanism-Driven Monitors for Preemptive Detection of LLM Training Instability
Related across the graph
paperFalsification, Not Exposure: An Internally Preregistered Placebo-Controlled Decomposition of Self-Repair Feedback in Frozen Small Code ModelspaperForm, Not Content? A Preregistered, Placebo-Controlled Evaluation of Learned Error-Conditioned Self-Repair Through Prompts and Weights in Frozen Small Code ModelsnewsStructured output reliability with LLMs — 3-month production learningsnewsA cheap trick for reliable structured output: feed the validation error back into the retrypaperMechanism-Driven Monitors for Preemptive Detection of LLM Training Instability