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cs.CV2025
REAR: Rethinking Visual Autoregressive Models via Generator-Tokenizer Consistency Regularization
Qiyuan He, Yicong Li, Haotian Ye +6
Visual autoregressive (AR) generation offers a promising path toward unifying vision and language models, yet its performance remains suboptimal against diffusion models. Prior wor…
cs.CV2024★ 1 cited
Reducing Hallucinations in Vision-Language Models via Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing +1
Hallucination poses a challenge to the deployment of large vision-language models (LVLMs) in applications. Unlike in large language models (LLMs), hallucination in LVLMs often aris…
cs.CV2024★ 1 cited
Geometric Trajectory Diffusion Models
Jiaqi Han, Minkai Xu, Aaron Lou +2
Generative models have shown great promise in generating 3D geometric systems, which is a fundamental problem in many natural science domains such as molecule and protein design. H…