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Seq@K: Evaluating Language Models Under Sequential Feedback

arXiv:2610.37859v1 Announce Type: new Abstract: Language-model agents differ fundamentally from prior intelligent systems in their ability to learn from natural language in context. This capability enables agents to iteratively refine their answers in response to feedback, a prevalent mode of opera…

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  1. 2026-10-31 04:00 · arXiv cs.AI
    Seq@K: Evaluating Language Models Under Sequential Feedback

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