Author

Wen-Tao Bao

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#artificial intelligence Preprint Sep 2026

MoEMB: Scaling Universal Multimodal Embeddings with Efficient Mixture-of-Experts Models

This work proposes MOEMB, which instead scales UME along the expert axis through mixture-of-experts (MoE), growing encoder capacity while preserving single-vector, non-autoregressive encoding, and conducts the first comprehensive study of adaptive computation for MoE-based embedding.

Xuan-Ming Cui, S. Mishra, Wen-Tao Bao et al. · 0 citations

#artificial intelligence Feb 2025

X-SG2S: Safe and Generalizable Gaussian Splatting with X-dimensional Watermarks

X-SG$^2$S is the first framework to unify 1D-to-3D watermarking and enable simultaneous multi-modal watermark embedding in 3DGS, achieving this with minimal rendering interference and zero modifications to parameters or pipelines.

Zihan Cheng, Wen-Tao Bao, Huiping Zhuang et al. · arXiv.org · 1 citation · ⚡1