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20242026
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cs.CV2026

MAC-Splat: Multi-Attribute Consistency for High-Fidelity Sparse-View Reconstruction

Jinqian Yang, Yichen Wu, Wanhua Li +4

Reconstructing high-fidelity 3D scenes from sparse-views remains a central problem in generalizable neural rendering. Existing generalizable 3D Gaussian Splatting (3DGS) methods of…

cs.CV2026

DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization

Haokun Lin, Xinle Jia, Haobo Xu +7

The MXFP4 microscaling format, which partitions tensors into blocks of 32 elements sharing an E8M0 scaling factor, has emerged as a promising substrate for efficient LLM inference,…

cs.CV2025

LRQ-DiT: Log-Rotation Post-Training Quantization of Diffusion Transformers for Image and Video Generation

Lianwei Yang, Haokun Lin, Tianchen Zhao +6

Diffusion Transformers (DiTs) have achieved impressive performance in text-to-image and text-to-video generation. However, their high computational cost and large parameter sizes p…

cs.CV20241 cited

DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers

Lianwei Yang, Haisong Gong, Haokun Lin +4

Vision Transformers (ViTs) have gained significant attention, but their high computing cost limits the practical applications. While post-training quantization (PTQ) reduces model…

cs.CV20245 cited

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Renrui Zhang, Dongzhi Jiang, Yichi Zhang +8

The remarkable progress of Multi-modal Large Language Models (MLLMs) has garnered unparalleled attention, due to their superior performance in visual contexts. However, their capab…