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Zhongyi Liu

9 papers hereh-index 8253 citations16 works total

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

author position
  • middle author8
  • last author1

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

fields
  • cs.LG4
  • cs.IR3
  • cs.CL2
same name
  • Zhongyi Liu — 5 papers, h 6
  • Zhongyi Liu — 3 papers, h 3
  • Zhongyi Liu — 1 paper, h 2
  • Zhongyi Liu — 1 paper, h 2
  • Zhongyi Liu — 1 paper, h 12

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 citedAutomatic Expert Selection for Multi-Scenario and Multi-Task Search

44 citations · 45 across the 9 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023★ 1 cited

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs

Ling Yang, Ye Tian, Minkai Xu +7

GNN-to-MLP distillation aims to utilize knowledge distillation (KD) to learn computationally-efficient multi-layer perceptron (student MLP) on graph data by mimicking the output re…

cs.LG2023

Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization

Ling Yang, Jiayi Zheng, Heyuan Wang +5

Out-of-distribution (OOD) graph generalization are critical for many real-world applications. Existing methods neglect to discard spurious or noisy features of inputs, which are ir…

cs.LG2023

GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning

Weifan Wang, Binbin Hu, Zhicheng Peng +5

Recently, the growth of service platforms brings great convenience to both users and merchants, where the service search engine plays a vital role in improving the user experience…

cs.LG2022★ 44 cited

Automatic Expert Selection for Multi-Scenario and Multi-Task Search

Xinyu Zou, Zhi Hu, Yiming Zhao +4

Multi-scenario learning (MSL) enables a service provider to cater for users' fine-grained demands by separating services for different user sectors, e.g., by user's geographical re…

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