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Fuzhen Zhuang

60 papers hereh-index 5116.4k citations210 works total

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

author position
  • first author3
  • middle author51
  • last author3

Across the 57 of 60 papers where every author was matched, so the position is known.

fields
  • cs.LG20
  • cs.IR18
  • cs.CL11
  • cs.AI3
  • cs.CV3
  • cs.CR1
same name
  • Fuzhen Zhuang — 59 papers, h 7
  • Fuzhen Zhuang — 11 papers, h 6
  • Fuzhen Zhuang — 3 papers, h 15
  • Fuzhen Zhuang — 3 papers, h 17
  • Fuzhen Zhuang — 2 papers, h 3
  • Fuzhen Zhuang — 2 papers, h 4

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

activity
20182026
most citedDeep Subdomain Adaptation Network for Image Classification

1.2k citations · 2.8k across the 60 of their papers we have counts for

collaborators
Showing 2022 · cs.CLShow all

4 papers · 2 filters

cs.CL2022★ 2 cited

Pruning Pre-trained Language Models Without Fine-Tuning

Ting Jiang, Deqing Wang, Fuzhen Zhuang +2

To overcome the overparameterized problem in Pre-trained Language Models (PLMs), pruning is widely used as a simple and straightforward compression method by directly removing unim…

cs.CL2022★ 4 cited

A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis

Wei Chen, Jinglong Du, Zhao Zhang +2

Recently, some span-based methods have achieved encouraging performances for joint aspect-sentiment analysis, which first extract aspects (aspect extraction) by detecting aspect bo…

cs.CL2022★ 3 cited

Exploiting Global and Local Hierarchies for Hierarchical Text Classification

Ting Jiang, Deqing Wang, Leilei Sun +3

Hierarchical text classification aims to leverage label hierarchy in multi-label text classification. Existing methods encode label hierarchy in a global view, where label hierarch…

cs.CL2022★ 12 cited

PromptBERT: Improving BERT Sentence Embeddings with Prompts

Ting Jiang, Jian Jiao, Shaohan Huang +7

We propose PromptBERT, a novel contrastive learning method for learning better sentence representation. We firstly analyze the drawback of current sentence embedding from original…

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