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Jian Chen

4 papers here

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

author position
  • first author1
  • middle author2
  • last author1

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

fields
  • cs.CV4
ORCID 0000-0003-0938-5704
same name
  • Jian Chen — 11 papers
  • Jian Chen — 9 papers, h 32
  • Jian Chen — 9 papers
  • Jian Chen — 7 papers, h 20
  • Jian Chen — 6 papers
  • Jian Chen — 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 citedEnhanced Long-Tailed Recognition with Contrastive CutMix Augmentation

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

collaborators

4 papers

cs.CV2024

MMR: Evaluating Reading Ability of Large Multimodal Models

Jian Chen, Ruiyi Zhang, Yufan Zhou +3

Large multimodal models (LMMs) have demonstrated impressive capabilities in understanding various types of image, including text-rich images. Most existing text-rich image benchmar…

cs.CV2024

LLaVA-Read: Enhancing Reading Ability of Multimodal Language Models

Ruiyi Zhang, Yufan Zhou, Jian Chen +3

Large multimodal language models have demonstrated impressive capabilities in understanding and manipulating images. However, many of these models struggle with comprehending inten…

cs.CV2024★ 1 cited

Enhanced Long-Tailed Recognition with Contrastive CutMix Augmentation

Haolin Pan, Yong Guo, Mianjie Yu +1

Real-world data often follows a long-tailed distribution, where a few head classes occupy most of the data and a large number of tail classes only contain very limited samples. In…

cs.CV2024★ 1 cited

TRINS: Towards Multimodal Language Models that Can Read

Ruiyi Zhang, Yanzhe Zhang, Jian Chen +4

Large multimodal language models have shown remarkable proficiency in understanding and editing images. However, a majority of these visually-tuned models struggle to comprehend th…

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