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20222026
most citedLongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression

13 citations · 90 across the 40 of their papers we have counts for

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cs.CV2026

Beyond Text Conditioning: A Systematic Study of MLLM-DiT Fusion for Video Generation

Yanbo Ding, Yijia Fan, Caihua Shan +8

Diffusion Transformers (DiTs) have become the dominant paradigm for high-fidelity video generation, yet their ability to perform high-level semantic planning remains limited. While…

cs.CV2026

MM-WebAgent: A Hierarchical Multimodal Web Agent for Webpage Generation

Yan Li, Zezi Zeng, Yifan Yang +12

The rapid progress of Artificial Intelligence Generated Content (AIGC) tools enables images, videos, and visualizations to be created on demand for webpage design, offering a flexi…

cs.CV2026

AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation

Ziwei Zhou, Zeyuan Lai, Rui Wang +6

Text-to-Audio-Video (T2AV) generation is rapidly becoming a core interface for media creation, yet its evaluation remains fragmented. Existing benchmarks largely assess audio and v…

cs.CV2025

MMInference: Accelerating Pre-filling for Long-Context VLMs via Modality-Aware Permutation Sparse Attention

Yucheng Li, Huiqiang Jiang, Chengruidong Zhang +8

The integration of long-context capabilities with visual understanding unlocks unprecedented potential for Vision Language Models (VLMs). However, the quadratic attention complexit…

cs.CV2025

Zoomer: Adaptive Image Focus Optimization for Black-box MLLM

Jiaxu Qian, Chendong Wang, Yifan Yang +16

Multimodal large language models (MLLMs) such as GPT-4o, Gemini Pro, and Claude 3.5 have enabled unified reasoning over text and visual inputs, yet they often hallucinate in real w…

cs.CV2025

HiTVideo: Hierarchical Tokenizers for Enhancing Text-to-Video Generation with Autoregressive Large Language Models

Ziqin Zhou, Yifan Yang, Yuqing Yang +7

Text-to-video generation poses significant challenges due to the inherent complexity of video data, which spans both temporal and spatial dimensions. It introduces additional redun…

cs.CV2025★ 1 cited

VoLUT: Efficient Volumetric streaming enhanced by LUT-based super-resolution

Chendong Wang, Anlan Zhang, Yifan Yang +5

3D volumetric video provides immersive experience and is gaining traction in digital media. Despite its rising popularity, the streaming of volumetric video content poses significa…

cs.CV2025

Region-Adaptive Sampling for Diffusion Transformers

Ziming Liu, Yifan Yang, Chengruidong Zhang +4

Diffusion models (DMs) have become the leading choice for generative tasks across diverse domains. However, their reliance on multiple sequential forward passes significantly limit…

cs.CV2024★ 2 cited

LLM2CLIP: Powerful Language Model Unlocks Richer Cross-Modality Representation

Weiquan Huang, Aoqi Wu, Yifan Yang +10

CLIP is a seminal multimodal model that maps images and text into a shared representation space through contrastive learning on billions of image-caption pairs. Inspired by the rap…

cs.CV2023

Unified Medical Image Pre-training in Language-Guided Common Semantic Space

Xiaoxuan He, Yifan Yang, Xinyang Jiang +6

Vision-Language Pre-training (VLP) has shown the merits of analysing medical images, by leveraging the semantic congruence between medical images and their corresponding reports. I…

cs.CV2023★ 10 cited

ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation

Yasheng Sun, Yifan Yang, Houwen Peng +5

While language-guided image manipulation has made remarkable progress, the challenge of how to instruct the manipulation process faithfully reflecting human intentions persists. An…

cs.CV2023★ 7 cited

Unsupervised Video Anomaly Detection for Stereotypical Behaviours in Autism

Jiaqi Gao, Xinyang Jiang, Yuqing Yang +2

Monitoring and analyzing stereotypical behaviours is important for early intervention and care taking in Autism Spectrum Disorder (ASD). This paper focuses on automatically detecti…

cs.CV2022

Attentive Mask CLIP

Yifan Yang, Weiquan Huang, Yixuan Wei +8

Image token removal is an efficient augmentation strategy for reducing the cost of computing image features. However, this efficient augmentation strategy has been found to adverse…