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Text-to-SQL models can now achieve significantly higher accuracy by grouping and ranking SQL candidates based on execution results, then strategically resampling when the initial pool is lacking.
Stop hand-crafting hints for RL agents: HiLL learns to generate adaptive hints that actually improve the agent's performance on the original task, not just the hinted one.
Forget prompt engineering – LSE trains LLMs to self-edit their own contexts at test time, outperforming even GPT-5 and Claude Sonnet 4.5 in Text-to-SQL and question answering.
