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Zhihong Chen

4 papers here

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

author position
  • first author3
  • middle author1

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

fields
  • cs.CV3
  • cs.CL1
ORCID 0000-0002-7056-1335
same name
  • Zhihong Chen — 14 papers, h 40
  • Zhihong Chen — 8 papers, h 12
  • Zhihong Chen — 3 papers
  • Zhihong Chen — 2 papers
  • Zhihong Chen — 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 citedTowards Unifying Medical Vision-and-Language Pre-training via Soft Prompts

4 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 1 cited

Advancing Visual Grounding with Scene Knowledge: Benchmark and Method

Zhihong Chen, Ruifei Zhang, Yibing Song +2

Visual grounding (VG) aims to establish fine-grained alignment between vision and language. Ideally, it can be a testbed for vision-and-language models to evaluate their understand…

cs.CV2023★ 2 cited

Bridging Vision and Language Encoders: Parameter-Efficient Tuning for Referring Image Segmentation

Zunnan Xu, Zhihong Chen, Yong Zhang +3

Parameter Efficient Tuning (PET) has gained attention for reducing the number of parameters while maintaining performance and providing better hardware resource savings, but few st…

cs.CL2023★ 1 cited

On the Difference of BERT-style and CLIP-style Text Encoders

Zhihong Chen, Guiming Hardy Chen, Shizhe Diao +2

Masked language modeling (MLM) has been one of the most popular pretraining recipes in natural language processing, e.g., BERT, one of the representative models. Recently, contrast…

cs.CV2023★ 4 cited

Towards Unifying Medical Vision-and-Language Pre-training via Soft Prompts

Zhihong Chen, Shizhe Diao, Benyou Wang +2

Medical vision-and-language pre-training (Med-VLP) has shown promising improvements on many downstream medical tasks owing to its applicability to extracting generic representation…

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