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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs

Haojian Huang, Harold Haodong Chen, Meng Luo +6

We introduce VidPair-Halluc, a new benchmark for evaluating video hallucination in large video models (LVMs) under rigorous and controlled conditions. Unlike previous benchmarks th…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

Structure-Aware Prototype Guided Trusted Multi-View Classification

Haojian Huang, Jiahao Shi, Zhe Liu +4

Trustworthy multi-view classification (TMVC) addresses the challenge of achieving reliable decision-making in complex scenarios where multi-source information is heterogeneous, inc…

cs.CV2025

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…

cs.CV2025

Hierarchical Fine-grained Preference Optimization for Physically Plausible Video Generation

Harold Haodong Chen, Haojian Huang, Qifeng Chen +2

Recent advancements in video generation have enabled the creation of high-quality, visually compelling videos. However, generating videos that adhere to the laws of physics remains…

cs.CV2025

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…

cs.CV2025

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…