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Ruiming Tang

3 papers here

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

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.IR3
ORCID 0000-0002-9224-2431
same name
  • Ruiming Tang — 79 papers, h 45
  • Ruiming Tang — 38 papers, h 18
  • Ruiming Tang — 37 papers, h 4
  • Ruiming Tang — 34 papers, h 16
  • Ruiming Tang — 21 papers, h 10
  • Ruiming Tang — 12 papers, h 5

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

most citedHow Can Recommender Systems Benefit from Large Language Models: A Survey

21 citations · 29 across the 3 of their papers we have counts for

collaborators

3 papers

cs.IR2024

Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark

Xiaopeng Li, Jingtong Gao, Pengyue Jia +7

Multi Scenario Recommendation (MSR) tasks, referring to building a unified model to enhance performance across all recommendation scenarios, have recently gained much attention. Ho…

cs.IR2023★ 21 cited

How Can Recommender Systems Benefit from Large Language Models: A Survey

Jianghao Lin, Xinyi Dai, Yunjia Xi +11

With the rapid development of online services, recommender systems (RS) have become increasingly indispensable for mitigating information overload. Despite remarkable progress, con…

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.