most citedQwen2.5-1M Technical Report

12 citations · 13 across the 34 of their papers we have counts for

collaborators

41 papers

cs.CV2026

RepForcing: Representation-Space Initialization for Autoregressive Video Distillation

Siming Fu, Zheming Fu, Lianrui Mu +3

Distilling pretrained video diffusion models into few-step autoregressive (AR) generators typically combines student initialization with distribution matching distillation (DMD). A…

cs.CV2026

REEL: Learning to Retrieve, Evaluate, and Evolve Visual Memory for Any Long-Horizon Multi-Shot Video Generation

Hang Xu, Guohui Zhang, Xiaoxiao Ma +7

Memory-based long-video generation aims to combine user control with long-range visual consistency. We organize this process into three functional components: a planner, an adapter…

cs.RO2026

WorldLine: Action-Driven Visual Simulation for Robotic Manipulation

Shenghe Zheng, Wenbo Li, Jiyao Zhang +4

Real-world robot learning is constrained by the cost of collecting experience and evaluating candidate behaviors. Video generation models offer a scalable foundation for visual sim…

cs.CV2026

EVO-WAM: Evolving World Action Models through Video-Action Verification

Shiyang Zhou, Xionghao Wu, Wenbo Li +11

Improving robot policies on new tasks without collecting additional expert demonstrations remains a central challenge in robot learning. World action models (WAMs) use broad video…

cs.CV2026

Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning

Yijun Yang, Shenghe Zheng, Wenbo Li +8

Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the physical world. We argue th…

cs.CV2026

Building Pretraining Data for World Models: An Unreal Engine-Based Pipeline for Action-Conditioned Video Generation

Haoyu Wang, Songchun Zhang, Haoran Li +3

Action-conditioned video models require large-scale visual data paired with control signals that are temporally aligned with the resulting scene transitions. Such supervision is di…

cs.CV2026

ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training

Xionghao Wu, Yijun Yang, Shiyang Zhou +17

Robotic manipulation faces a fundamental scaling challenge: robust generalization demands broad physical experience, yet action-labeled robot trajectories are expensive to collect…

cs.CV2026

Long-Horizon Audio-Visual Generation for Persistent Stories and Interactive Worlds

Nan Duan, Haoyang Huang, Weiyang Jin +13

Video generation is progressing beyond isolated clips toward long-form narratives and interactive worlds, requiring models to preserve identities, follow user controls, and remain…

cs.CV2026

EchoWM: Open and Enterable Omnimodal World Models

Songchun Zhang, Yaowei Li, Junhao Zhuang +19

We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, environmental sound, music an…

cs.CV2026

HalluScope: Fine-grained Hallucination Diagnosis for Multimodal Large Language Models

Weilin Jin, Mingyu Wang, Wenbo Li +5

Although Multimodal Large Language Models have achieved strong performance across a wide range of vision-language tasks, they still suffer from hallucinations, where model outputs…

cs.CV2026

JoyAI-Video-Edit: Real-Time Open-Ended Video Editing with Autoregressive Diffusion

Yicheng Xiao, Wenxun Dai, Xinran Qin +22

Real-time video editing requires low-latency causal generation with bounded computational resources while preserving source fidelity and long-term temporal consistency. We present…

cs.CV2026

Role-Break in Attention Heads: Understanding and Detecting Hallucinations in VLMs

Mingyu Wang, Weilin Jin, Wenbo Li +5

Despite remarkable progress in vision-language generation, Vision-Language Models (VLMs) remain prone to hallucinations, producing content that is inconsistent with or unsupported…

cs.CV2026

Self Gradient Forcing: Native Long Video Extrapolation

Junhao Zhuang, Shiyi Zhang, Yuxuan Bian +11

Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-tru…

cs.CV2026

Oxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On

Yong Liu, Xiaolong Fu, Zihang Xu +10

We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is fashion-native, built for t…

cs.CV2026

Geo3R: Mitigating Spatial Reasoning Hallucination in Multimodal Large Language Models

Mingyu Wang, Weilin Jin, Wenbo Li +3

Despite remarkable progress in visual understanding, Multimodal Large Language Models (MLLMs) remain prone to hallucinations when reasoning about spatial relationships, often produ…

cs.CV2026

Perceptual Flow Matching for Few-Step Generative Modeling

Chuyang Zhao, Yifei Song, Hongfa Wang +7

We propose Perceptual Flow Matching (PFM), a simple yet effective framework for few-step generation in flow-matching models. Rather than performing velocity regression in the conve…

cs.CV2026

Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization

Xiaoxuan He, Siming Fu, Zeyue Xue +9

Group Relative Policy Optimization has emerged as essential for aligning video diffusion models with human preferences, but faces a critical computational bottleneck: training a 14…

cs.CV2026

AnchorEdit: Maintaining Temporal Consistency in Multi-turn Image Editing via Causal Memory

Hang Xu, Xiaoxiao Ma, Guohui Zhang +7

Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successive steps. While existing resea…

cs.CV2026

Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions

Xin Lu, Luxury, Jie Huang +27

While recent autoregressive video diffusion models achieve remarkable streaming quality, they remain confined to low resolutions (e.g., 480P), leaving efficient, scalable, real-tim…

cs.AI2026

SpatialWorld: Benchmarking Interactive Spatial Reasoning of Multimodal Agents in Real-World Tasks

Hongcheng Gao, Hailong Qu, Jingyi Tang +18

Spatial reasoning is a foundational capability for multimodal large language models (MLLMs) to perceive and operate within the physical world. However, existing benchmarks predomin…

cs.CV2026

JoyAI-VL-Interaction: Real-Time Vision-Language Interaction Intelligence

Dingyu Yao, Junhao Zhou, Chenxu Yang +17

Many moments in the real world do not wait for a user to ask. A fire starts on a security monitor, an expression flickers across a video call, or a product a viewer wants flashes b…

cs.CV2026

Echo-Memory: A Controlled Study of Memory in Action World Models

Wayne King, Zeyue Xue, Yuxuan Bian +13

We present \textbf{Echo-Memory}, a controlled study of memory mechanisms in action-conditioned world models. These models generate multi-segment videos from a first frame, text pro…

cs.MM2026

Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation

Yuxuan Bian, Zeyue Xue, Songchun Zhang +9

We present Echo Infinity, an autoregressive (AR) framework towards real-time infinite video generation that employs a learnable evolving memory to dynamically filter, abstract, and…

cs.CV2026

Embodied3DBench: Benchmarking Low-Level Embodied Spatial Intelligence of Vision Language Models

Jiyao Zhang, Mingxu Zhang, Yitong Peng +8

Are current Vision Language Models (VLMs) ready to comprehend and reason about complex embodied interactions in 3D environments? We introduce Embodied3DBench, a robot-centric bench…