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Jiayin Xiao

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Book Open access Aug 2026

Retrv-MoE: Scaling Unified Multimodal Retrieval with Sparse Mixture-of-Experts

This work proposes Retrv-MoE, a unified retrieval architecture built upon sparse Mixture-of-Experts (MoE), and theoretically and empirically demonstrates that this conditional computation mechanism provides a structural remedy to optimization interference by decoupling the learning trajectories of conflicting tasks and...

Tongxu Lin, Jiayin Xiao · 0 citations
Book Open access Aug 2026

Retrv-MoE: Scaling Unified Multimodal Retrieval with Sparse Mixture-of-Experts

Unified multimodal retrieval aims to build a single system capable of handling diverse modalities, tasks, and domains. While recent approaches leveraging multimodal large language models (MLLMs) have shown promise, they face a fundamental dilemma between capacity and interference: scaling dense models improves semantic...

Tongxu Lin, Jiayin Xiao · 0 citations

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