14 papers
OpenCoF: Learning to Reason Through Video Generation
Xinyan Chen, Ziyu Guo, Renrui Zhang +2
Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video generation models offer a reaso…
GLEAM: Learning to Match and Explain in Cross-View Geo-Localization
Xudong Lu, Zhi Zheng, Yi Wan +11
Cross-View Geo-Localization (CVGL) focuses on identifying correspondences between images captured from distinct perspectives of the same geographical location. However, existing CV…
Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark
Ziyu Guo, Xinyan Chen, Renrui Zhang +7
Recent video generation models can produce high-fidelity, temporally coherent videos, indicating that they may encode substantial world knowledge. Beyond realistic synthesis, they…
Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step
Ziyu Guo, Renrui Zhang, Chengzhuo Tong +9
Chain-of-Thought (CoT) reasoning has been extensively explored in large models to tackle complex understanding tasks. However, it still remains an open question whether such strate…
Resurrect Mask AutoRegressive Modeling for Efficient and Scalable Image Generation
Yi Xin, Le Zhuo, Qi Qin +8
AutoRegressive (AR) models have made notable progress in image generation, with Masked AutoRegressive (MAR) models gaining attention for their efficient parallel decoding. However,…
T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT
Dongzhi Jiang, Ziyu Guo, Renrui Zhang +6
Recent advancements in large language models have demonstrated how chain-of-thought (CoT) and reinforcement learning (RL) can improve performance. However, applying such reasoning…