100 citations · 141 across the 6 of their papers we have counts for
7 papers
OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models
Jinze Bai, Rui Men, Hao Yang +15
Generalist models, which are capable of performing diverse multi-modal tasks in a task-agnostic way within a single model, have been explored recently. Being, hopefully, an alterna…
Pretrained Diffusion Models for Unified Human Motion Synthesis
Jianxin Ma, Shuai Bai, Chang Zhou
Generative modeling of human motion has broad applications in computer animation, virtual reality, and robotics. Conventional approaches develop separate models for different motio…
M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems
Zeyu Cui, Jianxin Ma, Chang Zhou +2
Industrial recommender systems have been growing increasingly complex, may involve \emph{diverse domains} such as e-commerce products and user-generated contents, and can comprise…
Learning to Rehearse in Long Sequence Memorization
Zhu Zhang, Chang Zhou, Jianxin Ma +4
Existing reasoning tasks often have an important assumption that the input contents can be always accessed while reasoning, requiring unlimited storage resources and suffering from…
M6: A Chinese Multimodal Pretrainer
Junyang Lin, Rui Men, An Yang +22
In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1.9TB images and 292GB texts that cover a wide range of domains. We pro…
Inductive Granger Causal Modeling for Multivariate Time Series
Yunfei Chu, Xiaowei Wang, Jianxin Ma +3
Granger causal modeling is an emerging topic that can uncover Granger causal relationship behind multivariate time series data. In many real-world systems, it is common to encounte…