Search

3 results for “MMLU-Redux”

1. Research · Agents

   Draft-KV ensures the receiver actually uses the sender's latent message

   Draft-KV: Learning Useful Latent Communication Between Language Models

   By sending key-value states from the sharer's draft, a lightweight interface boosts a 0.5B receiver to 78% on MMLU-Redux, and message-replacement tests confirm the gain comes from genuine information use.

   MMLU-Redux: 36.4% accuracy (as reported)

   29 Sept 2026City University of Hong Kong, University of Science and Technology of China, University of Electronic Science and Technology of China

2. 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

3. Research digest

   This Week in Agentic AI Research: Runtime Contracts Beat Model Intuition

   The strongest results move reliability from model reasoning into explicit state, memory, communication and audit mechanisms.

   1 Oct 2026