258 citations · 642 across the 18 of their papers we have counts for
18 papers
Qwen2 Technical Report
An Yang, Baosong Yang, Binyuan Hui +59
This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruct…
Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering Benchmark
Zhikun Xu, Yinghui Li, Ruixue Ding +7
How to better evaluate the capabilities of Large Language Models (LLMs) is the focal point and hot topic in current LLMs research. Previous work has noted that due to the extremely…
Controllable 3D Face Generation with Conditional Style Code Diffusion
Xiaolong Shen, Jianxin Ma, Chang Zhou +1
Generating photorealistic 3D faces from given conditions is a challenging task. Existing methods often rely on time-consuming one-by-one optimization approaches, which are not effi…
Qwen Technical Report
Jinze Bai, Shuai Bai, Yunfei Chu +45
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to hu…
JOTR: 3D Joint Contrastive Learning with Transformers for Occluded Human Mesh Recovery
Jiahao Li, Zongxin Yang, Xiaohan Wang +3
In this study, we focus on the problem of 3D human mesh recovery from a single image under obscured conditions. Most state-of-the-art methods aim to improve 2D alignment technologi…
TransHuman: A Transformer-based Human Representation for Generalizable Neural Human Rendering
Xiao Pan, Zongxin Yang, Jianxin Ma +2
In this paper, we focus on the task of generalizable neural human rendering which trains conditional Neural Radiance Fields (NeRF) from multi-view videos of different characters. T…
Global-to-Local Modeling for Video-based 3D Human Pose and Shape Estimation
Xiaolong Shen, Zongxin Yang, Xiaohan Wang +3
Video-based 3D human pose and shape estimations are evaluated by intra-frame accuracy and inter-frame smoothness. Although these two metrics are responsible for different ranges of…
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…
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Peng Wang, An Yang, Rui Men +7
In this work, we pursue a unified paradigm for multimodal pretraining to break the scaffolds of complex task/modality-specific customization. We propose OFA, a Task-Agnostic and Mo…
Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI
Jiangchao Yao, Shengyu Zhang, Yang Yao +15
Influenced by the great success of deep learning via cloud computing and the rapid development of edge chips, research in artificial intelligence (AI) has shifted to both of the co…
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-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis via Non-Autoregressive Generative Transformers
Zhu Zhang, Jianxin Ma, Chang Zhou +6
Conditional image synthesis aims to create an image according to some multi-modal guidance in the forms of textual descriptions, reference images, and image blocks to preserve, as…
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…
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems
Chang Zhou, Jianxin Ma, Jianwei Zhang +2
Deep candidate generation (DCG) that narrows down the collection of relevant items from billions to hundreds via representation learning has become prevalent in industrial recommen…
Learning Disentangled Representations for Recommendation
Jianxin Ma, Chang Zhou, Peng Cui +2
User behavior data in recommender systems are driven by the complex interactions of many latent factors behind the users' decision making processes. The factors are highly entangle…