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Zhen Fang

4 papers here

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

author position
  • middle author3
  • last author1

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

fields
  • cs.LG2
  • cs.CL1
  • cs.SE1
ORCID 0000-0002-7391-372X
same name
  • Zhen Fang — 10 papers
  • Zhen Fang — 5 papers
  • Zhen Fang — 3 papers
  • Zhen Fang — 2 papers
  • Zhen Fang — 1 paper
  • Zhen Fang — 1 paper

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 citedModerately Distributional Exploration for Domain Generalization

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

collaborators

4 papers

cs.SE2025

CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios

Shiting Huang, Zhen Fang, Zehui Chen +6

The ability of large language models (LLMs) to utilize external tools has enabled them to tackle an increasingly diverse range of tasks. However, as the tasks become more complex a…

cs.CL2023★ 1 cited

Continual Named Entity Recognition without Catastrophic Forgetting

Duzhen Zhang, Wei Cong, Jiahua Dong +4

Continual Named Entity Recognition (CNER) is a burgeoning area, which involves updating an existing model by incorporating new entity types sequentially. Nevertheless, continual le…

cs.LG2023★ 2 cited

SODA: Robust Training of Test-Time Data Adaptors

Zige Wang, Yonggang Zhang, Zhen Fang +3

Adapting models deployed to test distributions can mitigate the performance degradation caused by distribution shifts. However, privacy concerns may render model parameters inacces…

cs.LG2023★ 13 cited

Moderately Distributional Exploration for Domain Generalization

Rui Dai, Yonggang Zhang, Zhen Fang +2

Domain generalization (DG) aims to tackle the distribution shift between training domains and unknown target domains. Generating new domains is one of the most effective approaches…

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