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Xiangyu Zhao

9 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3
  • last author4

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.IR4
  • cs.LG2
  • cs.AI1
  • cs.CL1
  • physics.soc-ph1
ORCID 0000-0003-2926-4416
same name
  • Xiangyu Zhao — 42 papers, h 16
  • Xiangyu Zhao — 28 papers, h 10
  • Xiangyu Zhao — 24 papers, h 31
  • Xiangyu Zhao — 15 papers, h 8
  • Xiangyu Zhao — 13 papers, h 9
  • Xiangyu Zhao — 13 papers, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142025
most citedRecommender Systems in the Era of Large Language Models (LLMs)

422 citations · 534 across the 9 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.IR2023★ 7 cited

Embedding in Recommender Systems: A Survey

Maolin Wang, Xinjian Zhao, Wanyu Wang +9

Recommender systems have become an essential component of many online platforms, providing personalized recommendations to users. A crucial aspect is embedding techniques that conv…

cs.IR2023★ 422 cited

Recommender Systems in the Era of Large Language Models (LLMs)

Zihuai Zhao, Wenqi Fan, Jiatong Li +8

With the prosperity of e-commerce and web applications, Recommender Systems (RecSys) have become an important component of our daily life, providing personalized suggestions that c…

cs.AI2023

Tensorized Hypergraph Neural Networks

Maolin Wang, Yaoming Zhen, Yu Pan +5

Hypergraph neural networks (HGNN) have recently become attractive and received significant attention due to their excellent performance in various domains. However, most existing H…

cs.IR2023★ 8 cited

Multi-Task Deep Recommender Systems: A Survey

Yuhao Wang, Ha Tsz Lam, Yi Wong +8

Multi-task learning (MTL) aims at learning related tasks in a unified model to achieve mutual improvement among tasks considering their shared knowledge. It is an important topic i…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.