1 citations · 1 across the 6 of their papers we have counts for
6 papers
SuperValid: Capability-Aligned OOD Validation for Generalizable Downstream Scaling
Quanen Sun, Changxin Tian, Ke Shi +6
Scaling laws guide large language model training by relating compute to cross-entropy loss, and recent work further extends them to predict downstream benchmark performance. Howeve…
GUI-GenBench: Evaluating Image Generation Models as Interactive GUI Environments
Haodong Li, Jingwei Wu, Quan Sun +18
An image generation model used as a graphical user interface (GUI) environment must produce not only a plausible screen but also the correct response to an action. Existing visual-…
NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale
NextStep Team, Chunrui Han, Guopeng Li +47
Prevailing autoregressive (AR) models for text-to-image generation either rely on heavy, computationally-intensive diffusion models to process continuous image tokens, or employ ve…
Step1X-Edit: A Practical Framework for General Image Editing
Shiyu Liu, Yucheng Han, Peng Xing +21
In recent years, image editing models have witnessed remarkable and rapid development. The recent unveiling of cutting-edge multimodal models such as GPT-4o and Gemini2 Flash has i…
Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model
Guoqing Ma, Haoyang Huang, Kun Yan +112
We present Step-Video-T2V, a state-of-the-art text-to-video pre-trained model with 30B parameters and the ability to generate videos up to 204 frames in length. A deep compression…
Taming Teacher Forcing for Masked Autoregressive Video Generation
Deyu Zhou, Quan Sun, Yuang Peng +8
We introduce MAGI, a hybrid video generation framework that combines masked modeling for intra-frame generation with causal modeling for next-frame generation. Our key innovation,…