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20242026
most citedIs Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond

8 citations · 12 across the 39 of their papers we have counts for

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24 papers · 1 filter

cs.CV2026

Beyond One-Size-Fits-All: Sample-Adaptive Strategy Routing for Vision Token Pruning in MLLMs

Haiji Liang, Pengfei Zhou, Zhenglin Wan +3

Multimodal large language models (MLLMs) process hundreds or thousands of visual tokens per image, incurring prohibitive inference costs. While existing vision token pruning method…

cs.CV2026

SCOPE-Router: Cost-Aware Open-Set VLM Routing for Execution-Oriented Tasks

Tao Yu, Yifei Qu, Zhiqing Cui +14

Model routing aims to select the most suitable model from a candidate pool for each query, balancing quality and cost. Existing VLM routing research is limited to traditional VQA e…

cs.CV2026

Can We Defend Against AI-Generated Video Attacks on Real-World Crisis Events? A Systematic Evaluation of Detectors, Generators and Social Dissemination

Shuo Liang, Yixing Ma, Pengfei Zhou +33

Recent video generators can fabricate realistic depictions of wars, disasters, public emergencies, and other real-world crises, creating substantial risks of misinformation. Existi…

cs.CV2026

Dynamic Resolution Routing for Efficient Egocentric Grounding

Huixin Sun, Wangbo Zhao, Fanyue Wei +3

Egocentric visual grounding requires high-resolution inputs to localize small objects. However, scaling Multimodal Large Language Models to this domain is constrained by the excess…

cs.CV2026

WorldOlympiad: Can Your World Model Survive a Triathlon?

Yuke Zhao, Wangbo Zhao, Weijie Wang +8

We introduce WorldOlympiad, a benchmark for diagnosing video-based world models across physical faithfulness, geometric consistency, and interaction fidelity. While existing benchm…

cs.CV2026

GroupToM-Bench: Benchmarking Group Theory of Mind and Nonlinear Social Emergence in MLLMs

Weidong Tang, Jierui Li, Yueling Hou +7

True general intelligence requires not only a model of the physical world but also a social world model: the capacity to infer how individual mental states interact and crystallize…

cs.CV2026

HumanNOVA: Photorealistic, Universal and Rapid 3D Human Avatar Modeling from a Single Image

Hezhen Hu, Wangbo Zhao, Lanqing Guo +6

In this paper, we present HumanNOVA, a photorealistic, universal, and rapid model for generating 3D human avatars from a single RGB image. Achieving both photorealism and generaliz…

cs.CV2026

FARTrack: Fast Autoregressive Visual Tracking with High Performance

Guijie Wang, Tong Lin, Yifan Bai +4

Inference speed and tracking performance are two critical evaluation metrics in the field of visual tracking. However, high-performance trackers often suffer from slow processing s…

cs.CV2026

K-Sort Eval: Efficient Preference Evaluation for Visual Generation via Corrected VLM-as-a-Judge

Zhikai Li, Jiatong Li, Xuewen Liu +7

The rapid development of visual generative models raises the need for more scalable and human-aligned evaluation methods. While the crowdsourced Arena platforms offer human prefere…

cs.CV2025

RAPID^3: Tri-Level Reinforced Acceleration Policies for Diffusion Transformer

Wangbo Zhao, Yizeng Han, Zhiwei Tang +7

Diffusion Transformers (DiTs) excel at visual generation yet remain hampered by slow sampling. Existing training-free accelerators - step reduction, feature caching, and sparse att…

cs.CV2025

EA-ViT: Efficient Adaptation for Elastic Vision Transformer

Chen Zhu, Wangbo Zhao, Huiwen Zhang +9

Vision Transformers (ViTs) have emerged as a foundational model in computer vision, excelling in generalization and adaptation to downstream tasks. However, deploying ViTs to suppo…

cs.CV2025

Neural-Driven Image Editing

Pengfei Zhou, Jie Xia, Xiaopeng Peng +15

Traditional image editing typically relies on manual prompting, making it labor-intensive and inaccessible to individuals with limited motor control or language abilities. Leveragi…

cs.CV2025

REPA Works Until It Doesn't: Early-Stopped, Holistic Alignment Supercharges Diffusion Training

Ziqiao Wang, Wangbo Zhao, Yuhao Zhou +9

Diffusion Transformers (DiTs) deliver state-of-the-art image quality, yet their training remains notoriously slow. A recent remedy -- representation alignment (REPA) that matches D…

cs.CV2025

Unsupervised Learning for Class Distribution Mismatch

Pan Du, Wangbo Zhao, Xinai Lu +8

Class distribution mismatch (CDM) refers to the discrepancy between class distributions in training data and target tasks. Previous methods address this by designing classifiers to…

cs.CV2025

DD-Ranking: Rethinking the Evaluation of Dataset Distillation

Zekai Li, Xinhao Zhong, Samir Khaki +49

In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance co…

cs.CV2025

MDK12-Bench: A Multi-Discipline Benchmark for Evaluating Reasoning in Multimodal Large Language Models

Pengfei Zhou, Fanrui Zhang, Xiaopeng Peng +17

Multimodal reasoning, which integrates language and visual cues into problem solving and decision making, is a fundamental aspect of human intelligence and a crucial step toward ar…

cs.CV2025

Dynamic Vision Mamba

Mengxuan Wu, Zekai Li, Zhiyuan Liang +9

Mamba-based vision models have gained extensive attention as a result of being computationally more efficient than attention-based models. However, spatial redundancy still exists…

cs.CV2025

DyDiT++: Diffusion Transformers with Timestep and Spatial Dynamics for Efficient Visual Generation

Wangbo Zhao, Yizeng Han, Jiasheng Tang +6

Diffusion Transformer (DiT), an emerging diffusion model for visual generation, has demonstrated superior performance but suffers from substantial computational costs. Our investig…

cs.CV2025

PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models

Zhaopan Xu, Pengfei Zhou, Weidong Tang +7

Multimodal large language models (MLLMs) have achieved remarkable success in vision-language tasks, but their reliance on vast, internet-sourced data raises significant privacy and…

cs.CV2024

A Stitch in Time Saves Nine: Small VLM is a Precise Guidance for Accelerating Large VLMs

Wangbo Zhao, Yizeng Han, Jiasheng Tang +5

Vision-language models (VLMs) have shown remarkable success across various multi-modal tasks, yet large VLMs encounter significant efficiency challenges due to processing numerous…

cs.CV2024

Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training

Mingjia Shi, Yuhao Zhou, Ruiji Yu +8

Vision Mamba has shown close to state of the art performance on computer vision tasks, drawing much interest in increasing it's efficiency. A promising approach is token reduction…

cs.CV2024

Dynamic Diffusion Transformer

Wangbo Zhao, Yizeng Han, Jiasheng Tang +5

Diffusion Transformer (DiT), an emerging diffusion model for image generation, has demonstrated superior performance but suffers from substantial computational costs. Our investiga…

cs.CV2024★ 8 cited

Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond

Zheng Zhu, Xiaofeng Wang, Wangbo Zhao +15

General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual en…

cs.CV2024★ 4 cited

Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation

Wangbo Zhao, Jiasheng Tang, Yizeng Han +5

Existing parameter-efficient fine-tuning (PEFT) methods have achieved significant success on vision transformers (ViTs) adaptation by improving parameter efficiency. However, the e…