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Zhiheng Li

4 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.IR2
ORCID 0000-0002-1523-1114
same name
  • Zhiheng Li — 9 papers, h 11
  • Zhiheng Li — 9 papers, h 4
  • Zhiheng Li — 6 papers, h 7
  • Zhiheng Li — 4 papers, h 30
  • Zhiheng Li — 4 papers, h 2
  • Zhiheng Li — 4 papers, h 2

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 citedDual-interest Factorization-heads Attention for Sequential Recommendation

13 citations · 16 across the 4 of their papers we have counts for

collaborators

4 papers

cs.IR2023★ 13 cited

Dual-interest Factorization-heads Attention for Sequential Recommendation

Guanyu Lin, Chen Gao, Yu Zheng +6

Accurate user interest modeling is vital for recommendation scenarios. One of the effective solutions is the sequential recommendation that relies on click behaviors, but this is n…

cs.CV2022★ 2 cited

A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others

Zhiheng Li, Ivan Evtimov, Albert Gordo +5

Machine learning models have been found to learn shortcuts -- unintended decision rules that are unable to generalize -- undermining models' reliability. Previous works address thi…

cs.IR2022★ 1 cited

Mutual Harmony: Sequential Recommendation with Dual Contrastive Network

Guanyu Lin, Chen Gao, Yinfeng Li +6

With the outbreak of today's streaming data, the sequential recommendation is a promising solution to achieve time-aware personalized modeling. It aims to infer the next interacted…

cs.CV2022

Enhancing Multi-view Stereo with Contrastive Matching and Weighted Focal Loss

Yikang Ding, Zhenyang Li, Dihe Huang +2

Learning-based multi-view stereo (MVS) methods have made impressive progress and surpassed traditional methods in recent years. However, their accuracy and completeness are still s…

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