3 citations · 7 across the 14 of their papers we have counts for
10 papers · 1 filter
ChainV: Atomic Visual Hints Make Multimodal Reasoning Shorter and Better
Yuan Zhang, Ming Lu, Junwen Pan +4
Recent advances in multimodal reasoning models have demonstrated impressive capabilities across text and vision. However, even leading models exhibit redundant self-reflection when…
TimeSearch-R: Adaptive Temporal Search for Long-Form Video Understanding via Self-Verification Reinforcement Learning
Junwen Pan, Qizhe Zhang, Rui Zhang +5
Temporal search aims to identify a minimal set of relevant frames from tens of thousands based on a given query, serving as a foundation for accurate long-form video understanding.…
UniEdit-I: Training-free Image Editing for Unified VLM via Iterative Understanding, Editing and Verifying
Chengyu Bai, Jintao Chen, Xiang Bai +4
While Unified Vision-Language Models promise to synergistically combine the high-level semantic understanding of vision-language models with the generative fidelity of diffusion mo…
Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage
Junqing Lin, Jingwei Sun, Mingge Lu +1
Sparse Matrix-Vector Multiplication (SpMV) has become a critical performance bottleneck in the local deployment of sparse Large Language Models (LLMs), where inference predominantl…
Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs
Qizhe Zhang, Mengzhen Liu, Lichen Li +5
In multimodal large language models (MLLMs), the length of input visual tokens is often significantly greater than that of their textual counterparts, leading to a high inference c…
FastInit: Fast Noise Initialization for Temporally Consistent Video Generation
Chengyu Bai, Yuming Li, Zhongyu Zhao +5
Video generation has made significant strides with the development of diffusion models; however, achieving high temporal consistency remains a challenging task. Recently, FreeInit…
AutoV: Loss-Oriented Ranking for Visual Prompt Retrieval in LVLMs
Yuan Zhang, Chun-Kai Fan, Sicheng Yu +6
Inspired by text prompts in large language models, visual prompts have been explored to enhance the perceptual capabilities of large vision-language models (LVLMs). However, perfor…
UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens
Ruichuan An, Sihan Yang, Renrui Zhang +10
Personalized models have demonstrated remarkable success in understanding and generating concepts provided by users. However, existing methods use separate concept tokens for under…
ZoomV: Temporal Zoom-in for Efficient Long Video Understanding
Yuan Zhang, Junwen Pan, Rui Zhang +5
Long video understanding poses a fundamental challenge for large video-language models (LVLMs) due to the overwhelming number of frames and the risk of losing essential context thr…
MC-LLaVA: Multi-Concept Personalized Vision-Language Model
Ruichuan An, Sihan Yang, Ming Lu +9
Current vision-language models (VLMs) show exceptional abilities across diverse tasks, such as visual question answering. To enhance user experience, recent studies investigate VLM…