4 citations · 11 across the 17 of their papers we have counts for
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JUICE: Unified Multimodal Modeling in Pretrained Representation Spaces
Jiahan Li, Huangyuan Su, Shengbang Tong +9
Most unified multimodal models treat images and text asymmetrically: a pretrained language model generates text, an attached diffusion head generates images, and outputs that conta…
Purify Before You Align: Improving Representation Alignment for Diffusion Models
Yingheng Wang, Yaoqiang Li, Yaqin Wu +4
Representation alignment improves and accelerates diffusion training by encouraging intermediate features to match a pretrained visual encoder. However, standard alignment matches…
Latent Reasoning with Normalizing Flows
Guancheng Tu, Xiangjun Fu, Suhao Yu +5
Large language models often improve reasoning by generating explicit chain-of-thought (CoT), demonstrating the importance of intermediate computation. However, textual CoT forces t…
Multiplex Thinking: Reasoning via Token-wise Branch-and-Merge
Yao Tang, Li Dong, Yaru Hao +3
Large language models often solve complex reasoning tasks more effectively with Chain-of-Thought (CoT), but at the cost of long, low-bandwidth token sequences. Humans, by contrast,…