Expert-Level Sparsity and Robustness in Mixture-of-Experts Multimodal Evaluation

This report synthesises findings from 15 peer-reviewed papers addressing the following research question: Does expert-level sparsity in Mixture-of-Experts models maintain robustness on multimodal evaluation suites such as ScienceQA or MMMU compared to full-parameter inference. 6 claims were extracted from source literature; 6 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.7/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: Does expert-level sparsity in Mixture-of-Experts models maintain robustness on multimodal evaluation suites such as ScienceQA or MMMU compared to full-parameter inference?

Autonomous literature synthesis. Automated review score: 8.7/10. Full text and citation available at Assignee Research.