1 citations · 1 across the 5 of their papers we have counts for
11 papers
Swordsman: Entropy-Driven Adaptive Block Partition for Efficient Diffusion Language Models
Yu Zhang, Xinchen Li, Jialei Zhou +6
Block-wise decoding effectively improves the inference speed and quality in diffusion language models (DLMs) by combining inter-block sequential denoising and intra-block parallel…
Markovian Scale Prediction: A New Era of Visual Autoregressive Generation
Yu Zhang, Jingyi Liu, Yiwei Shi +4
Visual AutoRegressive modeling (VAR) based on next-scale prediction has revitalized autoregressive visual generation. Although its full-context dependency, i.e., modeling all previ…
Cross-Modal Distillation For Widely Differing Modalities
Cairong Zhao, Yufeng Jin, Zifan Song +3
Deep learning achieved great progress recently, however, it is not easy or efficient to further improve its performance by increasing the size of the model. Multi-modal learning ca…
Transformer-Based Person Search with High-Frequency Augmentation and Multi-Wave Mixing
Qilin Shu, Qixian Zhang, Qi Zhang +3
The person search task aims to locate a target person within a set of scene images. In recent years, transformer-based models in this field have made some progress. However, they s…
Improving Prediction Certainty Estimation for Reliable Early Exiting via Null Space Projection
Jianing He, Qi Zhang, Duoqian Miao +4
Early exiting has demonstrated great potential in accelerating the inference of pre-trained language models (PLMs) by enabling easy samples to exit at shallow layers, eliminating t…
Boosting Adversarial Transferability via Commonality-Oriented Gradient Optimization
Yanting Gao, Yepeng Liu, Junming Liu +4
Exploring effective and transferable adversarial examples is vital for understanding the characteristics and mechanisms of Vision Transformers (ViTs). However, adversarial examples…