1 citations · 2 across the 5 of their papers we have counts for
5 papers
WEAVE: Unleashing and Benchmarking the In-context Interleaved Comprehension and Generation
Wei Chow, Jiachun Pan, Yongyuan Liang +10
Recent advances in unified multimodal models (UMMs) have enabled impressive progress in visual comprehension and generation. However, existing datasets and benchmarks focus primari…
Selftok: Discrete Visual Tokens of Autoregression, by Diffusion, and for Reasoning
Bohan Wang, Zhongqi Yue, Fengda Zhang +15
We completely discard the conventional spatial prior in image representation and introduce a novel discrete visual tokenizer: Self-consistency Tokenizer (Selftok). At its design co…
Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought
Yi Peng, Peiyu Wang, Xiaokun Wang +12
We introduce Skywork R1V, a multimodal reasoning model extending the an R1-series Large language models (LLM) to visual modalities via an efficient multimodal transfer method. Leve…
Towards Understanding Why Data Augmentation Improves Generalization
Jingyang Li, Jiachun Pan, Kim-Chuan Toh +1
Data augmentation is a cornerstone technique in deep learning, widely used to improve model generalization. Traditional methods like random cropping and color jittering, as well as…
MEMO: Memory-Guided Diffusion for Expressive Talking Video Generation
Longtao Zheng, Yifan Zhang, Hanzhong Guo +6
Recent advances in video diffusion models have unlocked new potential for realistic audio-driven talking video generation. However, achieving seamless audio-lip synchronization, ma…