5 papers · 1 filter
Jailbreaks on Vision Language Model via Multimodal Reasoning
Aarush Noheria, Yuguang Yao
Vision-language models (VLMs) have become central to tasks such as visual question answering, image captioning, and text-to-image generation. However, their outputs are highly sens…
SuperFlow: Training Flow Matching Models with RL on the Fly
Kaijie Chen, Zhiyang Xu, Ying Shen +3
Recent progress in flow-based generative models and reinforcement learning (RL) has improved text-image alignment and visual quality. However, current RL training for flow models s…
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees
Shaoan Xie, Lingjing Kong, Yujia Zheng +5
Contrastive Language-Image Pre-training (CLIP)~\citep{radford2021learning} has emerged as a pivotal model in computer vision and multimodal learning, achieving state-of-the-art per…
LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer
Ying Shen, Zhiyang Xu, Jiuhai Chen +6
Recent advances in multimodal foundation models unifying image understanding and generation have opened exciting avenues for tackling a wide range of vision-language tasks within a…
R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation
Kaijie Chen, Zihao Lin, Zhiyang Xu +5
Reasoning is a fundamental capability often required in real-world text-to-image (T2I) generation, e.g., generating ``a bitten apple that has been left in the air for more than a w…