3 citations · 5 across the 4 of their papers we have counts for
5 papers
RA-CFGCache: From Branch-Level Criteria to Guided-Risk Control under Classifier-Free Guidance
Yiming Liu, Ben Wan, Tongxuan Liu +5
Diffusion models enable high-quality visual generation, but iterative denoising remains computationally expensive, especially under classifier-free guidance (CFG), which requires b…
RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference
Ben Wan, Yan Feng, Zihan Tang +4
DeepSeek-OCR leverages visual-text compression to reduce long-text processing costs and accelerate inference, yet visual tokens remain prone to redundant textual and structural inf…
FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing
Zihan Tang, Leqi Shen, Hui Chen +7
Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to encode dense documents incurs proh…
Pruning for Sparse Diffusion Models based on Gradient Flow
Ben Wan, Tianyi Zheng, Zhaoyu Chen +2
Diffusion Models (DMs) have impressive capabilities among generation models, but are limited to slower inference speeds and higher computational costs. Previous works utilize one-s…
EnfoMax: Domain Entropy and Mutual Information Maximization for Domain Generalized Face Anti-spoofing
Tianyi Zheng
The face anti-spoofing (FAS) method performs well under intra-domain setups. However, its cross-domain performance is unsatisfactory. As a result, the domain generalization (DG) me…