1 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
DiverseDiT++: Quantifying, Analyzing, and Promoting Representation Diversity in Diffusion Transformers
Binglei Li, Mengping Yang, Zhiyu Tan +4
Recent advances in Diffusion Transformers (DiTs) have enabled remarkable progress in visual synthesis, benefiting from their superior scalability. To facilitate DiTs' capability of…
Monkey King Bang: A Unified Scientific Multimodal Foundation Model
Hesen Chen, Xinyu Su, Xiaomeng Yang +11
Scientific discovery is increasingly shifting from isolated disciplines to multi-domain reasoning, and AI for science faces a similar transition. Existing systems are either specia…
Omni-Video 2: Scaling MLLM-Conditioned Diffusion for Unified Video Generation and Editing
Hao Yang, Zhiyu Tan, Jia Gong +7
We present Omni-Video 2, a scalable and computationally efficient model that connects pretrained multimodal large-language models (MLLMs) with video diffusion models for unified vi…
DiverseDiT: Towards Diverse Representation Learning in Diffusion Transformers
Mengping Yang, Zhiyu Tan, Binglei Li +3
Recent breakthroughs in Diffusion Transformers (DiTs) have revolutionized the field of visual synthesis due to their superior scalability. To facilitate DiTs' capability of capturi…
A unified multimodal understanding and generation model for cross-disciplinary scientific research
Xiaomeng Yang, Zhiyu Tan, Xiaohui Zhong +5
Scientific discovery increasingly relies on integrating heterogeneous, high-dimensional data across disciplines nowadays. While AI models have achieved notable success across vario…