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cs.LG2026
Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction
Hongkun Dou, Zike Chen, Fengji Li +2
Controllable generation with discrete diffusion models is often hindered by high computational overhead or the need for retraining. In this paper, we present \underline{\textbf{G}}…
cs.CV2026
Spatiotemporal Degradation-Aware 3D Gaussian Splatting for Realistic Underwater Scene Reconstruction
Shaohua Liu, Ning Gao, Zuoya Gu +3
Reconstructing realistic underwater scenes from underwater video remains a meaningful yet challenging task in the multimedia domain. The inherent spatiotemporal degradations in und…
cs.LG2026
Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes
Hongkun Dou, Zike Chen, Zeyu Li +3
Diffusion models have gained prominence as powerful generative tools for solving inverse problems due to their ability to model complex data distributions. However, existing method…