ErrorProbe introduces a self-improving pipeline for attributing semantic failures in LLM multi-agent systems to specific agents and steps via anomaly detection, backward tracing, and tool-grounded validation with verified episodic memory.
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Infherno deploys LLM agents with code execution and terminology tools to synthesize FHIR resources from unstructured clinical notes, matching human baseline performance on synthetic and real datasets.
citing papers explorer
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Towards Self-Improving Error Diagnosis in Multi-Agent Systems
ErrorProbe introduces a self-improving pipeline for attributing semantic failures in LLM multi-agent systems to specific agents and steps via anomaly detection, backward tracing, and tool-grounded validation with verified episodic memory.
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Infherno: End-to-end Agent-based FHIR Resource Synthesis from Free-form Clinical Notes
Infherno deploys LLM agents with code execution and terminology tools to synthesize FHIR resources from unstructured clinical notes, matching human baseline performance on synthetic and real datasets.