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NoveltyBench: Evaluating Language Models for Humanlike Diversity

Evaluates how well language models generate diverse, humanlike responses across multiple reasoning and generation tasks. This evaluation assesses whether LLMs can produce varied outputs rather than repetitive or uniform answers.

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OriginYiming Zhang, Harshita Diddee, Susan Holm et al.TopicsGeneral capabilityStatusimported

Can support

Not independently assessed by FronteraEval yet.

Cannot support by itself

No inference beyond the upstream source should be made until the protocol is reviewed.

Original sources