A credibility-scoring framework for multi-agent LLM systems, learning agent trustworthiness on the fly and weighting outputs accordingly, improves accuracy under adversarial conditions in some benchmarks.
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An Adversary-Resistant Multi-Agent LLM System via Credibility Scoring
A credibility-scoring framework for multi-agent LLM systems, learning agent trustworthiness on the fly and weighting outputs accordingly, improves accuracy under adversarial conditions in some benchmarks.