14 papers
GEAR: Guided End-to-End AutoRegression for Image Synthesis
Bin Lin, Zheyuan Liu, Chenguo Lin +8
Visual generative models are typically trained in two stages. A tokenizer is first trained for reconstruction and then frozen, after which a generator is trained on its discrete in…
LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
Xinwu Ye, Yicheng Mao, Yuxuan Liao +16
Current chemical large language models (LLMs) predominantly rely on explicit Chain-of-Thought (CoT) to solve complex reasoning problems. However, forcing nonverbal tacit chemical l…
OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning
Yunyang Ge, Xianyi He, Zezhong Zhang +4
Diffusion Transformers achieve strong video generation quality, but the quadratic cost of full attention limits efficiency. We introduce OSP-Next, an efficient text-to-video genera…
Helios: Real Real-Time Long Video Generation Model
Shenghai Yuan, Yuanyang Yin, Zongjian Li +3
We introduce Helios, the first 14B video generation model that runs at 19.5 FPS on a single NVIDIA H100 GPU and supports minute-scale generation while matching the quality of a str…
iFSQ: Improving FSQ for Image Generation with 1 Line of Code
Bin Lin, Zongjian Li, Yuwei Niu +9
The field of image generation is currently bifurcated into autoregressive (AR) models operating on discrete tokens and diffusion models utilizing continuous latents. This divide, r…
Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
Team Seedance, Heyi Chen, Siyan Chen +194
Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…