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Rex Ying

67 papers hereh-index 3018.1k citations53 works total

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

author position
  • first author4
  • middle author36
  • last author24

Across the 64 of 67 papers where every author was matched, so the position is known.

fields
  • cs.LG38
  • cs.AI7
  • cs.CL5
  • cs.CV4
  • cs.IR4
  • q-bio.BM2
same name
  • Rex Ying — 14 papers, h 11
  • Rex Ying — 7 papers, h 6
  • Rex Ying — 4 papers
  • Rex Ying — 4 papers, h 4
  • Rex Ying — 3 papers, h 3
  • Rex Ying — 3 papers, h 3

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
20182026
most citedHyperbolic Graph Convolutional Neural Networks

266 citations · 459 across the 44 of their papers we have counts for

collaborators
Showing cs.IRShow all

4 papers · 1 filter

cs.IR2026

CoPersona: Collaborative Persona Graphs for Robust LLM Personalization

Yangtian Zhang, Leyao Wang, Hiren Madhu +3

Real-world LLM personalization is often constrained by sparse and skewed user histories: most users provide only a handful of interactions, while even frequent users' logs capture…

cs.IR2026

HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation

Hiren Madhu, Ngoc Bui, Ali Maatouk +6

Embedding geometry plays a fundamental role in retrieval quality, yet dense retrievers for retrieval-augmented generation (RAG) remain largely confined to Euclidean space. However,…

cs.IR2024

Breaking Information Cocoons: A Hyperbolic Framework for Balancing Exploration and Exploitation in Recommender Systems

Qiyao Ma, Menglin Yang, Mingxuan Ju +3

Modern recommender systems often create information cocoons, restricting users' exposure to diverse content. The central challenge is to balance content exploration and exploitatio…

cs.IR2018

Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Rex Ying, Ruining He, Kaifeng Chen +3

Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. However, making these methods pract…

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