Author

Hongyu Zhang

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Preprint Aug 2026

REFLEX: Rethinking MoE Inference as Refinement-Aware Compute Allocation in Diffusion Language Models

REFLEX is proposed, a training-free method that keeps the default router unchanged while reorganizing expert computation around the evolving refinement process, and introduces a coarse-to-fine hierarchy for expert-budget allocation that aligns computation with block-relative refinement roles while using the Frontier-Pr...

Xiang-Wen Xia, Chen Yan, Yiming Zhang et al. · 0 citations

Preprint Aug 2026

Beyond Global Routing Aggregation: Phase-Aware Expert Merging for MoE Vision-Language Models

Mixture-of-experts vision-language models (MoE-VLMs) increase model capacity with sparse expert activation, yet deployment requires storing the full expert pool. Training-free expert merging reduces this burden, and many routing-based methods aggregate routing statistics across all tokens to determine merge compatibili...

Hong-Yu Zhang, Cheng Yan, Xiang-Wen Xia et al. · 0 citations