activity
20242026
most citedAffineQuant: Affine Transformation Quantization for Large Language Models

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Seedance 2.0: Advancing Video Generation for World Complexity

Team Seedance, De Chen, Liyang Chen +168

Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…

cs.CV2026

Flow caching for autoregressive video generation

Yuexiao Ma, Xuzhe Zheng, Jing Xu +9

Autoregressive models, often built on Transformer architectures, represent a powerful paradigm for generating ultra-long videos by synthesizing content in sequential chunks. Howeve…

cs.CV2025

PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models

Tianchen Zhao, Ke Hong, Xinhao Yang +8

In visual generation, the quadratic complexity of attention mechanisms results in high memory and computational costs, especially for longer token sequences required in high-resolu…

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.LG2024★ 1 cited

AffineQuant: Affine Transformation Quantization for Large Language Models

Yuexiao Ma, Huixia Li, Xiawu Zheng +6

The significant resource requirements associated with Large-scale Language Models (LLMs) have generated considerable interest in the development of techniques aimed at compressing…