Papers with diagnostic approaches

2 papers
Towards Self-Improving Error Diagnosis in Multi-Agent Systems (2026.findings-acl)

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Challenge: Existing diagnostic approaches rely on expensive expert annotations and ”LLM-as-a-judge” paradigms.
Approach: They propose a framework for semantic failure attribution that identifies responsible agents and the originating error step.
Outcome: The proposed framework outperforms baselines in step-level localization and validation.
Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL (2026.findings-acl)

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Challenge: Large Language Models (LLMs) have been successful in Text-to-SQL tasks, but their deployment in real-world environments is hindered by latent reliability issues.
Approach: They propose a framework to autonomously uncover latent failure patterns in LLM-based Text-to-SQL generation.
Outcome: The proposed framework uncovers a substantial number of failure cases on state-of-the-art open-source LLMs.

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