AI Research
Seq@K: Evaluating Language Models Under Sequential Feedback
Evaluating language models as they learn from sequential feedback
Language-model agents differ fundamentally from prior intelligent systems in their ability to learn from natural language in context.
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ArXiv CS.AI
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ArXiv CS.AI
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Language-model agents can learn from natural language within a conversation, unlike prior intelligent systems described here. Evaluating them under sequential feedback can help assess this distinctive ability.
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