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20242026
most citedBLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

1 citations · 2 across the 10 of their papers we have counts for

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cs.CV2026

PerceptionComp: A Video Benchmark for Complex Perception-Centric Reasoning

Shaoxuan Li, Zhixuan Zhao, Hanze Deng +9

We introduce PerceptionComp, a manually annotated benchmark for complex, long-horizon, perception-centric video reasoning. PerceptionComp is designed so that no single moment is su…

cs.CV2026

Unified Text-Image Generation with Weakness-Targeted Post-Training

Jiahui Chen, Philippe Hansen-Estruch, Xiaochuang Han +7

Unified multimodal generation architectures that jointly produce text and images have recently emerged as a promising direction for text-to-image (T2I) synthesis. However, many exi…

cs.CV2025

GenEval 2: Addressing Benchmark Drift in Text-to-Image Evaluation

Amita Kamath, Kai-Wei Chang, Ranjay Krishna +3

Automating Text-to-Image (T2I) model evaluation is challenging; a judge model must be used to score correctness, and test prompts must be selected to be challenging for current T2I…

cs.CV2025

Self-Improving VLM Judges Without Human Annotations

Inna Wanyin Lin, Yushi Hu, Shuyue Stella Li +5

Effective judges of Vision-Language Models (VLMs) are crucial for model development. Current methods for training VLM judges mainly rely on large-scale human preference annotations…

cs.CV2025★ 1 cited

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Jiuhai Chen, Zhiyang Xu, Xichen Pan +10

Unifying image understanding and generation has gained growing attention in recent research on multimodal models. Although design choices for image understanding have been extensiv…

cs.CV2025

Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models

Xu Ma, Peize Sun, Haoyu Ma +22

Autoregressive (AR) models, long dominant in language generation, are increasingly applied to image synthesis but are often considered less competitive than Diffusion-based models.…