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Xiaohan Yu

10 papers hereh-index 463 citations11 works total

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

author position
  • first author6
  • middle author3
  • last author1

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.IR6
  • cs.AI2
  • cs.CL1
  • cs.CV1
same name
  • Xiaohan Yu — 12 papers, h 15
  • Xiaohan Yu — 9 papers, h 8
  • Xiaohan Yu — 4 papers
  • Xiaohan Yu — 3 papers, h 2
  • Xiaohan Yu — 2 papers, h 11
  • Xiaohan Yu — 2 papers, h 4

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
20242026
most citedRA-Rec: An Efficient ID Representation Alignment Framework for LLM-based Recommendation

1 citations · 3 across the 10 of their papers we have counts for

collaborators
Showing 2024 · cs.IRShow all

4 papers · 2 filters

cs.IR2024

Explainable CTR Prediction via LLM Reasoning

Xiaohan Yu, Li Zhang, Chong Chen

Recommendation Systems have become integral to modern user experiences, but lack transparency in their decision-making processes. Existing explainable recommendation methods are hi…

cs.IR2024

Break the ID-Language Barrier: An Adaption Framework for LLM-based Sequential Recommendation

Xiaohan Yu, Li Zhang, Xin Zhao +1

The recent breakthrough of large language models (LLMs) in natural language processing has sparked exploration in recommendation systems, however, their limited domain-specific kno…

cs.IR2024★ 1 cited

RA-Rec: An Efficient ID Representation Alignment Framework for LLM-based Recommendation

Xiaohan Yu, Li Zhang, Xin Zhao +2

Large language models (LLM) have recently emerged as a powerful tool for a variety of natural language processing tasks, bringing a new surge of combining LLM with recommendation s…

cs.IR2024

Multi-Tower Multi-Interest Recommendation with User Representation Repel

Tianyu Xiong, Xiaohan Yu

In the era of information overload, the value of recommender systems has been profoundly recognized in academia and industry alike. Multi-interest sequential recommendation, in par…

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