Search

Any time Past 24 hours Past week Past monthSort:Relevance Newest

Benchmark

MMLU-Redux

Reported in 3 papers on Zotpaper. The latest, each as the paper states it:

Role prompts help language models only under the right conditions0.87 accuracy
Post-training multi-token prediction heads match joint pretraining with far less data2.64 MAL
Draft-KV ensures the receiver actually uses the sender's latent message78.04% accuracy

All benchmarks →

1 result for “MMLU-Redux”

Research · Language models
Role prompts help language models only under the right conditions
Cognitive Enhancement: Rethinking the Necessity of Role-Playing for Large Language Models
Across multilingual knowledge benchmarks, persona prompting varied with model capacity, subject and language, while combining equivalent prompts across languages produced more consistent results.
MMLU-Redux: 0.87 accuracy (as reported)
7 Oct 2026Xiamen University, Tongyi Lab, The Chinese University of Hong Kong