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Xiaoye Qu

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#machine learning Preprint Oct 2026

Smoothing the Top-k Exposure Boundary for Sparse Mixture-of-Experts

Sparse Mixture-of-Experts models scale parameter capacity efficiently while maintaining a fixed compute budget per token. However, traditional training paradigms enforce a static choice of top-$k$ experts, which converts a continuous routing distribution into a rigid step function. This constraint introduces a brittle...

Yun-Kai Chai, Tong Zhu, Xiaoye Qu et al. · 0 citations
Preprint Aug 2026

MetaReason: Precise Interleaved Multimodal Reasoning via Editing Meta Information for Solving Geometry Problems

This work proposes MetaReason, a framework for multimodal reasoning in plane geometry that leverages structured meta-information to enable accurate auxiliary-line construction and demonstrates that MetaReason significantly outperforms existing open-source models and achieves competitive performance against proprietary...

Penghao Yin, Haomin Wang, Qihong Tang et al. · 0 citations

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