#database-queries2 articles

2 articles

AINeutralarXiv – CS AI · 4d ago6/104

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From Conversation to Query Execution: Benchmarking User and Tool Interactions for EHR Database Agents

Researchers introduced EHR-ChatQA, a new benchmark for testing AI agents that interact with Electronic Health Record databases through natural language queries. The benchmark reveals significant reliability gaps in current state-of-the-art LLMs, with success rates dropping substantially when consistency across multiple trials is required.

AINeutralarXiv – CS AI · 4d ago5/103

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AWARE-US: Preference-Aware Infeasibility Resolution in Tool-Calling Agents

Researchers developed AWARE-US, a system to improve AI agents' ability to handle failed database queries by intelligently relaxing the least important user constraints rather than simply returning 'no results'. The system uses three LLM-based methods to infer constraint importance from dialogue, achieving up to 56% accuracy in correct constraint relaxation.