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Yunyi Zhang

4 papers here

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

author position
  • sole author1
  • middle author3

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

fields
  • cs.CL3
  • math.ST1
ORCID 0000-0003-2863-5529
same name
  • Yunyi Zhang — 9 papers, h 15
  • Yunyi Zhang — 6 papers
  • Yunyi Zhang — 2 papers
  • Yunyi Zhang — 1 paper, 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 citedEffective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts

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

collaborators

4 papers

cs.CL2024

Seed-Guided Fine-Grained Entity Typing in Science and Engineering Domains

Yu Zhang, Yunyi Zhang, Yanzhen Shen +5

Accurately typing entity mentions from text segments is a fundamental task for various natural language processing applications. Many previous approaches rely on massive human-anno…

cs.CL2023★ 1 cited

Ontology Enrichment for Effective Fine-grained Entity Typing

Siru Ouyang, Jiaxin Huang, Pranav Pillai +3

Fine-grained entity typing (FET) is the task of identifying specific entity types at a fine-grained level for entity mentions based on their contextual information. Conventional me…

math.ST2023

Statistical inference of high-dimensional vector autoregressive time series with non-i.i.d. innovations

Yunyi Zhang

Independent or i.i.d. innovations is an essential assumption in the literature for analyzing a vector time series. However, this assumption is either too restrictive for a real-lif…

cs.CL2023★ 1 cited

Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts

Yu Zhang, Yunyi Zhang, Martin Michalski +3

Instead of mining coherent topics from a given text corpus in a completely unsupervised manner, seed-guided topic discovery methods leverage user-provided seed words to extract dis…

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