1 citations · 1 across the 6 of their papers we have counts for
9 papers
Unlocking Token Rewards via Training-Free Reward Attribution
Sitong Wu, Haoru Tan, Bin Xia +6
In this paper, we propose an extremely efficient, training-free method to extract token-level reward signals directly from an existing deep reward model. Our core idea is to attrib…
DreamOmni3: Scribble-based Editing and Generation
Bin Xia, Bohao Peng, Jiyang Liu +8
Recently unified generation and editing models have achieved remarkable success with their impressive performance. These models rely mainly on text prompts for instruction-based ed…
DreamOmni2: Multimodal Instruction-based Editing and Generation
Bin Xia, Bohao Peng, Yuechen Zhang +10
Recent advancements in instruction-based image editing and subject-driven generation have garnered significant attention, yet both tasks still face limitations in meeting practical…
DreamVE: Unified Instruction-based Image and Video Editing
Bin Xia, Jiyang Liu, Yuechen Zhang +6
Instruction-based editing holds vast potential due to its simple and efficient interactive editing format. However, instruction-based editing, particularly for video, has been cons…
VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning
Senqiao Yang, Junyi Li, Xin Lai +3
Recent advancements in vision-language models (VLMs) have improved performance by increasing the number of visual tokens, which are often significantly longer than text tokens. How…
Does Your Vision-Language Model Get Lost in the Long Video Sampling Dilemma?
Tianyuan Qu, Longxiang Tang, Bohao Peng +3
The rise of Large Vision-Language Models (LVLMs) has significantly advanced video understanding. However, efficiently processing long videos remains a challenge due to the ``Sampli…
Generative Video Propagation
Shaoteng Liu, Tianyu Wang, Jui-Hsien Wang +8
Large-scale video generation models have the inherent ability to realistically model natural scenes. In this paper, we demonstrate that through a careful design of a generative vid…
DreamOmni: Unified Image Generation and Editing
Bin Xia, Yuechen Zhang, Jingyao Li +5
Currently, the success of large language models (LLMs) illustrates that a unified multitasking approach can significantly enhance model usability, streamline deployment, and foster…
VisionZip: Longer is Better but Not Necessary in Vision Language Models
Senqiao Yang, Yukang Chen, Zhuotao Tian +4
Recent advancements in vision-language models have enhanced performance by increasing the length of visual tokens, making them much longer than text tokens and significantly raisin…