35 citations · 43 across the 11 of their papers we have counts for
13 papers
Transition Models: Rethinking the Generative Learning Objective
Zidong Wang, Yiyuan Zhang, Xiaoyu Yue +4
A fundamental dilemma in generative modeling persists: iterative diffusion models achieve outstanding fidelity, but at a significant computational cost, while efficient few-step al…
Native-Resolution Image Synthesis
Zidong Wang, Lei Bai, Xiangyu Yue +2
We introduce native-resolution image synthesis, a novel generative modeling paradigm that enables the synthesis of images at arbitrary resolutions and aspect ratios. This approach…
Multimodal Long Video Modeling Based on Temporal Dynamic Context
Haoran Hao, Jiaming Han, Yiyuan Zhang +1
Recent advances in Large Language Models (LLMs) have led to significant breakthroughs in video understanding. However, existing models still struggle with long video processing due…
Breaking the Encoder Barrier for Seamless Video-Language Understanding
Handong Li, Yiyuan Zhang, Longteng Guo +2
Most Video-Large Language Models (Video-LLMs) adopt an encoder-decoder framework, where a vision encoder extracts frame-wise features for processing by a language model. However, t…
Vision Search Assistant: Empower Vision-Language Models as Multimodal Search Engines
Zhixin Zhang, Yiyuan Zhang, Xiaohan Ding +1
Search engines enable the retrieval of unknown information with texts. However, traditional methods fall short when it comes to understanding unfamiliar visual content, such as ide…
Scaling Up Your Kernels: Large Kernel Design in ConvNets towards Universal Representations
Yiyuan Zhang, Xiaohan Ding, Xiangyu Yue
This paper proposes the paradigm of large convolutional kernels in designing modern Convolutional Neural Networks (ConvNets). We establish that employing a few large kernels, inste…
Explore the Limits of Omni-modal Pretraining at Scale
Yiyuan Zhang, Handong Li, Jing Liu +1
We propose to build omni-modal intelligence, which is capable of understanding any modality and learning universal representations. In specific, we propose a scalable pretraining p…
InteractiveVideo: User-Centric Controllable Video Generation with Synergistic Multimodal Instructions
Yiyuan Zhang, Yuhao Kang, Zhixin Zhang +3
We introduce , a user-centric framework for video generation. Different from traditional generative approaches that operate based on user-provided images…
Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities
Yiyuan Zhang, Xiaohan Ding, Kaixiong Gong +3
We propose to improve transformers of a specific modality with irrelevant data from other modalities, e.g., improve an ImageNet model with audio or point cloud datasets. We would l…
OneLLM: One Framework to Align All Modalities with Language
Jiaming Han, Kaixiong Gong, Yiyuan Zhang +6
Multimodal large language models (MLLMs) have gained significant attention due to their strong multimodal understanding capability. However, existing works rely heavily on modality…
Online Vectorized HD Map Construction using Geometry
Zhixin Zhang, Yiyuan Zhang, Xiaohan Ding +2
The construction of online vectorized High-Definition (HD) maps is critical for downstream prediction and planning. Recent efforts have built strong baselines for this task, howeve…
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
Xiaohan Ding, Yiyuan Zhang, Yixiao Ge +4
Large-kernel convolutional neural networks (ConvNets) have recently received extensive research attention, but two unresolved and critical issues demand further investigation. 1) T…
Beyond One-Preference-Fits-All Alignment: Multi-Objective Direct Preference Optimization
Zhanhui Zhou, Jie Liu, Jing Shao +4
A single language model, even when aligned with labelers through reinforcement learning from human feedback (RLHF), may not suit all human preferences. Recent approaches therefore…