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Stop guessing agent performance: use database execution as a training reward
◆ 85RelevanceOn a story from Hugging Face10h ago
Relying on LLM-as-a-judge for data tasks is often brittle and expensive. Using objective database execution success as a reward signal allows you to fine-tune agents for verifiable accuracy in SQL and data workflows.
Takeaways
- Replace subjective LLM feedback with objective database execution rewards.
- Use ThinkingBox to bridge the gap between query results and RL training.
- Post-training is becoming the standard for specialized agent performance.
Read the original at huggingface.co
Turning Database Grading into RL Rewards: Post-Training Agents with ThinkingBox
fmode.me/n/turning-database-grading-into-rl-rewards-post-training-agents-with-thinkingbox
Written by Founder Mode using gemini-3-flash-preview, from the publisher's own summary. We link the original rather than reproduce it — the reporting belongs to Hugging Face.
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