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Chang Zhou
Chang Zhou
Alibaba Group; Peking University (zhouchang@pku.edu.cn)
Verified email at pku.edu.cn
Title
Cited by
Cited by
Year
Deep Interest Evolution Network for Click-Through Rate Prediction
G Zhou, N Mou, Y Fan, Q Pi, W Bian, C Zhou, X Zhu, K Gai
AAAI 2019, 2019
10632019
Qwen Technical Report
J Bai, S Bai, Y Chu, Z Cui, K Dang, X Deng, Y Fan, W Ge, Y Han, F Huang, ...
https://arxiv.org/abs/2309.16609, 2023
9972023
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
P Wang, A Yang, R Men, J Lin, S Bai, Z Li, J Ma, C Zhou*, J Zhou, H Yang
ICML 2022, 2022
9932022
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
J Bai*, S Bai*, S Yang*, S Wang, S Tan, P Wang, J Lin, C Zhou*, J Zhou
arXiv preprint arXiv:2308.12966, 2023
841*2023
CogView: Mastering Text-to-Image Generation via Transformers
M Ding, Z Yang, W Hong, W Zheng, C Zhou, D Yin, J Lin, X Zou, Z Shao, ...
NeurIPS 2021, 2021
6562021
ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation
C Zhou, J Bai, J Song, X Liu, Z Zhao, X Chen, J Gao
AAAI 2018, 2017
3502017
Learning Disentangled Representations for Recommendation
J Ma*, C Zhou*, P Cui, H Yang, W Zhu
NeurIPS 2019, 2019
3422019
AliGraph: A Comprehensive Graph Neural Network Platform
R Zhu, K Zhao, H Yang, W Lin, C Zhou, B Ai, Y Li, J Zhou
VLDB 2019, 2019
3062019
Cognitive Graph for Multi-Hop Reading Comprehension at Scale
M Ding, C Zhou, Q Chen, H Yang, J Tang
ACL 2019, 2019
2882019
Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks
Q Lv, M Ding, Q Liu, Y Chen, W Feng, S He, C Zhou, J Jiang, Y Dong, ...
KDD 2021, 2021
2732021
Controllable Multi-Interest Framework for Recommendation
Y Cen, J Zhang, X Zou, C Zhou, H Yang, J Tang
KDD 2020, 2020
2692020
Scalable graph embedding for asymmetric proximity
C Zhou, Y Liu, X Liu, Z Liu, J Gao
AAAI 2017 31 (1), 2017
2432017
Disentangled Self-Supervision in Sequential Recommenders
J Ma, C Zhou, H Yang, P Cui, X Wang, W Zhu
KDD 2020, 2020
2132020
Understanding Negative Sampling in Graph Representation Learning
Z Yang, M Ding, C Zhou, H Yang, J Zhou, J Tang
KDD 2020, 2020
1942020
M6: A Chinese Multimodal Pretrainer
J Lin*, R Men*, A Yang*, C Zhou, M Ding, Y Zhang, P Wang, A Wang, ...
https://arxiv.org/abs/2103.00823, 2021
166*2021
M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems
Z Cui∗, J Ma∗, C Zhou, J Zhou, H Yang
https://arxiv.org/abs/2205.08084, 2022
1652022
CogLTX: Applying BERT to Long Texts
M Ding, C Zhou, H Yang, J Tang
NeurIPS 2020, 2020
1622020
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems
C Zhou*, J Ma*, J Zhang*, J Zhou, H Yang
KDD 2021, 2021
1492021
Qwen2 technical report
A Yang, B Yang, B Hui, B Zheng, B Yu, C Zhou, C Li, C Li, D Liu, F Huang, ...
arXiv preprint arXiv:2407.10671, 2024
1352024
Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
Z Yuan*, H Yuan*, C Li, G Dong, C Tan, C Zhou, J Zhou
arXiv preprint arXiv:2308.01825, 2023
1142023
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