2 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
Know When to Explore: Difficulty-Aware Certainty as a Guide for LLM Reinforcement Learning
Ang Li, Zhihang Yuan, Yang Zhang +2
Reinforcement Learning with Verifiable Feedback (RLVF) has become a key technique for enhancing the reasoning abilities of Large Language Models (LLMs). However, its reliance on sp…
SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling
Yi Guo, Wei Wang, Zhihang Yuan +8
Generative models like Flow Matching have achieved state-of-the-art performance but are often hindered by a computationally expensive iterative sampling process. To address this, r…
LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing
Xiaonan Nie, Qibin Liu, Fangcheng Fu +6
Larger transformer models always perform better on various tasks but require more costs to scale up the model size. To efficiently enlarge models, the mixture-of-experts (MoE) arch…
Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Ye Bai, Haonan Chen, Jitong Chen +35
We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regr…