most citedSeedance 1.0: Exploring the Boundaries of Video Generation Models

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

LoL: Longer than Longer, Scaling Video Generation to Hour

Justin Cui, Jie Wu, Ming Li +6

Recent research in long-form video generation has shifted from bidirectional to autoregressive models, yet these methods commonly suffer from error accumulation and a loss of long-…

cs.CV2025

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…

cs.CV2025

Self-Forcing++: Towards Minute-Scale High-Quality Video Generation

Justin Cui, Jie Wu, Ming Li +6

Diffusion models have revolutionized image and video generation, achieving unprecedented visual quality. However, their reliance on transformer architectures incurs prohibitively h…

cs.CV20251 cited

Seedance 1.0: Exploring the Boundaries of Video Generation Models

Yu Gao, Haoyuan Guo, Tuyen Hoang +41

Notable breakthroughs in diffusion modeling have propelled rapid improvements in video generation, yet current foundational model still face critical challenges in simultaneously b…

cs.CV2025

Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model

Team Seawead, Ceyuan Yang, Zhijie Lin +52

This technical report presents a cost-efficient strategy for training a video generation foundation model. We present a mid-sized research model with approximately 7 billion parame…

cs.IR2025

IU4Rec: Interest Unit-Based Product Organization and Recommendation for E-Commerce Platform

Wenhao Wu, Xiaojie Li, Lin Wang +8

Most recommendation systems typically follow a product-based paradigm utilizing user-product interactions to identify the most engaging items for users. However, this product-based…