Ang Li

According to our database, Ang Li authored at least 8 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning.

Jun Hu, Wenwen Xia, Xiaolu Zhang, Chilin Fu, Weichang Wu, Zhaoxin Huan, Ang Li, Zuoli Tang, Jun Zhou

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset.

Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang, Chenliang Li, Fajie Yuan

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

2023

AntM²C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction.

Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang

CoRR, 2023

Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System.

Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Xu Min

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation.

Zhaoxin Huan, Ang Li, Xiaolu Zhang, Xu Min, Jieyu Yang, Yong He, Jun Zhou

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Global-Aware Model-Free Self-distillation for Recommendation System.

Ang Li, Jian Hu, Wei Lu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Liang Zhang, Lihong Gu

Proceedings of the Database Systems for Advanced Applications, 2023

2022

Attribute-Conditioned Face Swapping Network for Low-Resolution Images.

Ang Li, Jian Hu, Chilin Fu, Xiaolu Zhang, Jun Zhou

Proceedings of the IEEE International Conference on Acoustics, 2022

GFlow-FT: Pick a Child Network via Gradient Flow for Efficient Fine-Tuning in Recommendation Systems.

Ke Ding, Yong He, Xin Dong, Jieyu Yang, Liang Zhang, Ang Li, Xiaolu Zhang, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022