12 citations · 12 across the 13 of their papers we have counts for
15 papers
AffineTok: Semantic Affine Consistency for Diffusion-Friendly Visual Tokenizer
Junqiu Yu, Pandeng Li, Yikai Wang +11
Visual tokenizers increasingly inject semantic supervision into latent spaces to make downstream diffusion easier. Yet how these semantics should be organized to facilitate denoisi…
WanSong v1.0 Technical Report
Binghui Chen, Pandeng Li, Yu Liu +1
Music generation foundation models have recently attracted significant industry attention. However, achieving efficient generation and high-fidelity long-form audio while supportin…
Video = World + Event Stream
Lianghua Huang, Zhi-Fan Wu, Yupeng Shi +24
We present Wan-Streamer v0.3, which reframes our native-streaming interaction model under a single organizing view: a video is a world plus an event stream. The world is the persis…
Wan-Streamer v0.2: Higher Resolution, Same Latency
Lianghua Huang, Zhi-Fan Wu, Yupeng Shi +23
We present Wan-Streamer v0.2, a latency-preserving upgrade of the native-streaming, end-to-end audio-visual interaction model. v0.2 keeps the v0.1 modeling formulation, but raises…
Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models
Lianghua Huang, Zhi-Fan Wu, Wei Wang +22
We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex audio-visual interaction. W…
DiffusionOPD: A Unified Perspective of On-Policy Distillation in Diffusion Models
Quanhao Li, Junqiu Yu, Kaixun Jiang +7
Reinforcement learning has emerged as a powerful tool for improving diffusion-based text-to-image models, but existing methods are largely limited to single-task optimization. Exte…
AIBench: Evaluating Visual-Logical Consistency in Academic Illustration Generation
Zhaohe Liao, Kaixun Jiang, Zhihang Liu +11
Although image generation has boosted various applications via its rapid evolution, whether the state-of-the-art models are able to produce ready-to-use academic illustrations for…
GenAgent: Scaling Text-to-Image Generation via Agentic Multimodal Reasoning
Kaixun Jiang, Yuzheng Wang, Junjie Zhou +6
We introduce GenAgent, unifying visual understanding and generation through an agentic multimodal model. Unlike unified models that face expensive training costs and understanding-…
ShowTable: Unlocking Creative Table Visualization with Collaborative Reflection and Refinement
Zhihang Liu, Xiaoyi Bao, Pandeng Li +7
While existing generation and unified models excel at general image generation, they struggle with tasks requiring deep reasoning, planning, and precise data-to-visual mapping abil…
UniLiP: Adapting CLIP for Unified Multimodal Understanding, Generation and Editing
Hao Tang, Chenwei Xie, Xiaoyi Bao +4
In this paper, we propose UniLIP, a unified framework that adapts CLIP for multimodal understanding, generation and editing. Although CLIP excels at understanding, it lacks reconst…
Wan: Open and Advanced Large-Scale Video Generative Models
Team Wan, Ang Wang, Baole Ai +58
This report presents Wan, a comprehensive and open suite of video foundation models designed to push the boundaries of video generation. Built upon the mainstream diffusion transfo…
Rethinking Video Tokenization: A Conditioned Diffusion-based Approach
Nianzu Yang, Pandeng Li, Liming Zhao +8
Existing video tokenizers typically use the traditional Variational Autoencoder (VAE) architecture for video compression and reconstruction. However, to achieve good performance, i…
Hybrid-Level Instruction Injection for Video Token Compression in Multi-modal Large Language Models
Zhihang Liu, Chen-Wei Xie, Pandeng Li +5
Recent Multi-modal Large Language Models (MLLMs) have been challenged by the computational overhead resulting from massive video frames, often alleviated through compression strate…
UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface
Hao Tang, Chenwei Xie, Haiyang Wang +5
Generalist models have achieved remarkable success in both language and vision-language tasks, showcasing the potential of unified modeling. However, effectively integrating fine-g…
CAPability: A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughness
Zhihang Liu, Chen-Wei Xie, Bin Wen +9
Visual captioning benchmarks have become outdated with the emergence of modern multimodal large language models (MLLMs), as the brief ground-truth sentences and traditional metrics…