{"slug": "self-refining-prompt-induction-for-streaming-text-to-sql", "title": "Self-Refining Prompt Induction for Streaming Text-to-SQL", "summary": "A new arXiv paper (2611.00960v1) presents Self-Refining Prompt Induction (SRPI), an offline method that turns text-to-SQL generation failures into reusable dialect instructions while keeping model weights fixed, evaluated on Confluent Cloud Flink SQL. Across seven Generators, the same induced prompt raised mean judge scores by 7.1 to 19.2 percentage points, including an increase from 85.3% to 97.5% for the induction model, and a separate compression study cut prompt length by 52.7% at a cost of 0.19 percentage points. The evaluation used a controlled synthetic workload seeded by 30 expert-written examples, with 335 induction examples and 257 questions from held-out domains, and an assistant using the induced prompt is now in early access.", "body_md": "arXiv:2611.00960v1 Announce Type: new \nAbstract: Text-to-SQL assistants for streaming engines must handle dialect-specific types, windowing rules, and temporal semantics, including constructs poorly handled by generic prompts. We present Self-Refining Prompt Induction (SRPI), an offline method that converts generation failures into reusable dialect instructions while keeping model weights fixed. A Refiner revises the Generator's prompt using reference-conditioned feedback from three LLM judges; a sampled regression guard checks earlier successes, and a separate Compressor reduces prompt length. Inference uses the frozen prompt without retrieval or query repair. We evaluate cross-domain and cross-model transfer on Confluent Cloud Flink SQL using a controlled synthetic workload seeded by 30 expert-written examples, with 335 induction examples and 257 questions from held-out domains. The same induced prompt improves mean judge scores across seven Generators by 7.1-19.2 percentage points, including an increase from 85.3% to 97.5% for the induction model. A separate compression study reduces prompt length by 52.7% with a 0.19-percentage-point score decrease. An assistant using the induced prompt is in early access, with initial user feedback to inform subsequent refinement.", "url": "https://wpnews.pro/news/self-refining-prompt-induction-for-streaming-text-to-sql", "canonical_source": "https://www.machinebrief.com/news/self-refining-prompt-induction-for-streaming-text-to-sql-faq2", "published_at": "2026-11-04 05:00:00+00:00", "updated_at": "2026-11-04 06:21:19.551263+00:00", "lang": "en", "topics": ["large-language-models", "ai-research", "natural-language-processing", "ai-tools"], "entities": ["Self-Refining Prompt Induction", "Confluent Cloud Flink SQL", "arXiv"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/self-refining-prompt-induction-for-streaming-text-to-sql", "markdown": "https://wpnews.pro/news/self-refining-prompt-induction-for-streaming-text-to-sql.md", "text": "https://wpnews.pro/news/self-refining-prompt-induction-for-streaming-text-to-sql.txt", "jsonld": "https://wpnews.pro/news/self-refining-prompt-induction-for-streaming-text-to-sql.jsonld"}}