1 citations · 1 across the 15 of their papers we have counts for
17 papers
Dual Exam: Controlled Evaluation of Multimodal Agents and World Models
Zhefan Rao, Meng Chu, Xuan Zhang +93
World Models (WMs) can support Multimodal Agents (MAs) through simulated experience, while Agent trajectories can inform World Model refinement. Evaluating this interaction require…
SolveEdit: Benchmarking Visual Problem Solving in Generative Models
Wenjie Shu, Yexin Liu, Harold Haodong Chen +9
Machine intelligence is often evaluated through abstract reasoning problems, yet many real-world problems are visual, such as arranging objects, repairing layouts, or tracing route…
The Past Frames the Future: Memory for Autoregressive Video Generation
Harold Haodong Chen, Rongjin Guo, Disen Lan +22
Advances in generative models have improved video fidelity, enabling long-horizon generation, interactive world modeling, and evolving visual environments. Autoregressive (AR) vide…
A Latent Distribution Perspective on Evaluating and Improving Latent Generative Models
Xianghong Fang, Wenjie Shu, Tongda Xu +3
In latent generative models, reconstruction quality is often assumed to correlate with generative performance. However, reconstruction FID (rFID) can exhibit weak or even negative…
GenRouter: Unified Workflow Routing for Agentic Image Generation
Harold Haodong Chen, Zhiyu Hou, Wen-Jie Shu +4
The rapid evolution of text-to-image (T2I) generation models has effectively solved the foundational challenge of raw pixel synthesis, shifting the community's focus toward fulfill…
Show, Don't Tell: Morphing Latent Reasoning into Image Generation
Harold Haodong Chen, Xinxiang Yin, Wen-Jie Shu +6
Text-to-image (T2I) generation has achieved remarkable progress, yet existing methods often lack the ability to dynamically reason and refine during generation--a hallmark of human…
LoopViT: Scaling Visual ARC with Looped Transformers
Wen-Jie Shu, Xuerui Qiu, Rui-Jie Zhu +3
Recent advances in visual reasoning have leveraged vision transformers to tackle the ARC-AGI benchmark. However, we argue that the feed-forward architecture, where computational de…
TiViBench: Benchmarking Think-in-Video Reasoning for Video Generative Models
Harold Haodong Chen, Disen Lan, Wen-Jie Shu +10
The rapid evolution of video generative models has shifted their focus from producing visually plausible outputs to tackling tasks requiring physical plausibility and logical consi…
AlignVid: Training-Free Attention Scaling for Semantic Fidelity in Text-Guided Image-to-Video Generation
Yexin Liu, Wen-Jie Shu, Zile Huang +6
Text-guided image-to-video generation has made substantial progress, yet it still struggles to execute text-specified edits that require substantial changes to a reference image (\…
Enhancing Diffusion-based Restoration Models via Difficulty-Adaptive Reinforcement Learning with IQA Reward
Xiaogang Xu, Ruihang Chu, Jian Wang +6
Reinforcement Learning (RL) has recently been incorporated into diffusion models, e.g., tasks such as text-to-image. However, directly applying existing RL methods to diffusion-bas…
ScalingAR: Scaling Confidence for Autoregressive Image Generation
Harold Haodong Chen, Xianfeng Wu, Wen-Jie Shu +4
Test-time strategies have shown remarkable success in improving large language models, but their application to next-token prediction (NTP) autoregressive (AR) image generation rem…
VideoGen-of-Thought: Step-by-step generating multi-shot video with minimal manual intervention
Mingzhe Zheng, Yongqi Xu, Haojian Huang +8
Current video generation models excel at short clips but fail to produce cohesive multi-shot narratives due to disjointed visual dynamics and fractured storylines. Existing solutio…
Temporal Regularization Makes Your Video Generator Stronger
Harold Haodong Chen, Haojian Huang, Xianfeng Wu +5
Temporal quality is a critical aspect of video generation, as it ensures consistent motion and realistic dynamics across frames. However, achieving high temporal coherence and dive…
LightGen: Efficient Image Generation through Knowledge Distillation and Direct Preference Optimization
Xianfeng Wu, Yajing Bai, Haoze Zheng +8
Recent advances in text-to-image generation have primarily relied on extensive datasets and parameter-heavy architectures. These requirements severely limit accessibility for resea…
VideoGen-of-Thought: Step-by-step generating multi-shot video with minimal manual intervention
Mingzhe Zheng, Yongqi Xu, Haojian Huang +8
Current video generation models excel at short clips but fail to produce cohesive multi-shot narratives due to disjointed visual dynamics and fractured storylines. Existing solutio…
Exploring the Low-Pass Filtering Behavior in Image Super-Resolution
Haoyu Deng, Zijing Xu, Yule Duan +3
Deep neural networks for image super-resolution (ISR) have shown significant advantages over traditional approaches like the interpolation. However, they are often criticized as 'b…
CMT: Cross Modulation Transformer with Hybrid Loss for Pansharpening
Wen-Jie Shu, Hong-Xia Dou, Rui Wen +2
Pansharpening aims to enhance remote sensing image (RSI) quality by merging high-resolution panchromatic (PAN) with multispectral (MS) images. However, prior techniques struggled t…