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Yichi Zhang

4 papers here

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

author position
  • first author1
  • middle author3

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

fields
  • cs.AI2
  • cs.CL1
  • cs.CV1
ORCID 0000-0002-4292-6835
same name
  • Yichi Zhang — 8 papers
  • Yichi Zhang — 6 papers
  • Yichi Zhang — 5 papers
  • Yichi Zhang — 5 papers
  • Yichi Zhang — 5 papers
  • Yichi Zhang — 4 papers

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 citedRethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment

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

collaborators

4 papers

cs.CV2023★ 1 cited

Competitive Ensembling Teacher-Student Framework for Semi-Supervised Left Atrium MRI Segmentation

Yuyan Shi, Yichi Zhang, Shasha Wang

Semi-supervised learning has greatly advanced medical image segmentation since it effectively alleviates the need of acquiring abundant annotations from experts and utilizes unlabe…

cs.AI2023★ 2 cited

Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment

Zhuo Chen, Lingbing Guo, Yin Fang +6

As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to identify identical entities across disparate knowledge graphs (KGs) by exploiting assoc…

cs.CL2023★ 1 cited

CausE: Towards Causal Knowledge Graph Embedding

Yichi Zhang, Wen Zhang

Knowledge graph embedding (KGE) focuses on representing the entities and relations of a knowledge graph (KG) into the continuous vector spaces, which can be employed to predict the…

cs.AI2023

Mastering Asymmetrical Multiplayer Game with Multi-Agent Asymmetric-Evolution Reinforcement Learning

Chenglu Sun, Yichi Zhang, Yu Zhang +4

Asymmetrical multiplayer (AMP) game is a popular game genre which involves multiple types of agents competing or collaborating with each other in the game. It is difficult to train…

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