PQR is a dual-module iterative framework that generates diverse and realistic queries to elicit failures in QA agents, detecting 23-78% more unhelpful responses than prior methods.
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
R-CAI inverts constitutional AI to automatically generate diverse toxic data for LLM red teaming, with probability clamping improving output coherence by 15% while preserving adversarial strength.
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PQR: A Framework to Generate Diverse and Realistic User Queries that Elicit QA Agent Failures
PQR is a dual-module iterative framework that generates diverse and realistic queries to elicit failures in QA agents, detecting 23-78% more unhelpful responses than prior methods.
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Reverse Constitutional AI: A Framework for Controllable Toxic Data Generation via Probability-Clamped RLAIF
R-CAI inverts constitutional AI to automatically generate diverse toxic data for LLM red teaming, with probability clamping improving output coherence by 15% while preserving adversarial strength.