288 citations · 299 across the 16 of their papers we have counts for
12 papers · 1 filter
Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention
Wenhu Zhang, Yiming Wu, Huanyu Wang +6
Diffusion Language Models (DLMs) enable globally coherent, bidirectional, and controllable text generation, offering advantages over traditional autoregressive LLMs, while scaling…
CoLVR: Enhancing Exploratory Latent Visual Reasoning via Contrastive Optimization
Ziyang Ding, Linjian Meng, Yiming Wu +3
Due to the potential for exploratory reasoning of Latent Visual Reasoning, recent works tend to enable MLLMs (Multimodal Large Language Models) to perform visual reasoning by propa…
Mass Concept Erasure in Diffusion Models with Concept Hierarchy
Jiahang Tu, Ye Li, Yiming Wu +3
The success of diffusion models has raised concerns about the generation of unsafe or harmful content, prompting concept erasure approaches that fine-tune modules to suppress speci…
Versatile Video Representation via Feed-Forward 2D Gaussian Splatting Tokenization
Zhenghao Chen, Zicong Chen, Lei Liu +2
Recent video representation methods that rely on fixed-grid, patch-wise tokenization often exhibit limited versatility.Spatially, uniformly allocating a fixed number of tokens ofte…
Towards Consumer-Grade Cybersickness Prediction: Multi-Model Alignment for Real-Time Vision-Only Inference
Yitong Zhu, Zhuowen Liang, Yiming Wu +2
Cybersickness remains a major obstacle to the widespread adoption of immersive virtual reality (VR), particularly in consumer-grade environments. While prior methods rely on invasi…
MoTe: Learning Motion-Text Diffusion Model for Multiple Generation Tasks
Yiming Wu, Wei Ji, Kecheng Zheng +2
Recently, human motion analysis has experienced great improvement due to inspiring generative models such as the denoising diffusion model and large language model. While the exist…
Towards Small Object Editing: A Benchmark Dataset and A Training-Free Approach
Qihe Pan, Zhen Zhao, Zicheng Wang +5
A plethora of text-guided image editing methods has recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models especially St…
Individual Content and Motion Dynamics Preserved Pruning for Video Diffusion Models
Yiming Wu, Zhenghao Chen, Huan Wang +1
The high computational cost and slow inference time are major obstacles to deploying Video Diffusion Models (VDMs). To overcome this, we introduce a new Video Diffusion Model Compr…
PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis
Zicheng Wang, Zhenghao Chen, Yiming Wu +3
Point cloud analysis has seen substantial advancements due to deep learning, although previous Transformer-based methods excel at modeling long-range dependencies on this task, the…
SOEDiff: Efficient Distillation for Small Object Editing
Yiming Wu, Qihe Pan, Zhen Zhao +3
In this paper, we delve into a new task known as small object editing (SOE), which focuses on text-based image inpainting within a constrained, small-sized area. Despite the remark…
Training-Free Unsupervised Prompt for Vision-Language Models
Sifan Long, Linbin Wang, Zhen Zhao +4
Prompt learning has become the most effective paradigm for adapting large pre-trained vision-language models (VLMs) to downstream tasks. Recently, unsupervised prompt tuning method…
Progressive Classifier and Feature Extractor Adaptation for Unsupervised Domain Adaptation on Point Clouds
Zicheng Wang, Zhen Zhao, Yiming Wu +2
Unsupervised domain adaptation (UDA) is a critical challenge in the field of point cloud analysis. Previous works tackle the problem either by feature extractor adaptation to enabl…