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20152025
most citedSlimmable Neural Networks

235 citations · 350 across the 18 of their papers we have counts for

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Showing cs.CVShow all

22 papers · 1 filter

cs.CV20252 cited

Seedream 4.0: Toward Next-generation Multimodal Image Generation

Team Seedream, :, Yunpeng Chen +48

We introduce Seedream 4.0, an efficient and high-performance multimodal image generation system that unifies text-to-image (T2I) synthesis, image editing, and multi-image compositi…

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

SeedEdit 3.0: Fast and High-Quality Generative Image Editing

Peng Wang, Yichun Shi, Xiaochen Lian +5

We introduce SeedEdit 3.0, in companion with our T2I model Seedream 3.0, which significantly improves over our previous SeedEdit versions in both aspects of edit instruction follow…

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.CV2025

Seedream 3.0 Technical Report

Yu Gao, Lixue Gong, Qiushan Guo +28

We present Seedream 3.0, a high-performance Chinese-English bilingual image generation foundation model. We develop several technical improvements to address existing challenges in…

cs.CV2025

Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

Lixue Gong, Xiaoxia Hou, Fanshi Li +25

Rapid advancement of diffusion models has catalyzed remarkable progress in the field of image generation. However, prevalent models such as Flux, SD3.5 and Midjourney, still grappl…