STEMMA: an adversarial multi-agent framework for evaluating self-identity consistency in LLMs
Read the original at arxiv.org→arXiv:2608.08164v1 Announce Type: new Abstract: Knowledge Distillation is a widely adopted technique in the training and fine-tuning of large language models (LLMs) enabling transfer of structured information and...
Original headline: "STEMMA: An Adversarial Multi-Agent Framework for Evaluating Self-Identity Consistency in LLMs"
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- Aug 11, 04:00 UTC arXiv cs.CL lead source STEMMA: An Adversarial Multi-Agent Framework for Evaluating Self-Identity Consistency in LLMs