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Jianbo Yuan

4 papers here

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

author position
  • middle author4

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

fields
  • cs.CV2
  • cs.LG1
  • cs.SD1
ORCID 0000-0002-8905-7438
same name
  • Jianbo Yuan — 22 papers, h 12
  • Jianbo Yuan — 5 papers, h 20
  • Jianbo Yuan — 3 papers, h 3
  • Jianbo Yuan — 2 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 citedHiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention

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

collaborators

4 papers

cs.CV2023

Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete Tokens

Yuxiao Chen, Jianbo Yuan, Yu Tian +5

Contrastive learning-based vision-language pre-training approaches, such as CLIP, have demonstrated great success in many vision-language tasks. These methods achieve cross-modal a…

cs.SD2023

CAT: Causal Audio Transformer for Audio Classification

Xiaoyu Liu, Hanlin Lu, Jianbo Yuan +1

The attention-based Transformers have been increasingly applied to audio classification because of their global receptive field and ability to handle long-term dependency. However,…

cs.CV2023★ 11 cited

HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention

Shijie Geng, Jianbo Yuan, Yu Tian +2

The success of large-scale contrastive vision-language pretraining (CLIP) has benefited both visual recognition and multimodal content understanding. The concise design brings CLIP…

cs.LG2023★ 2 cited

Efficient Attention via Control Variates

Lin Zheng, Jianbo Yuan, Chong Wang +1

Random-feature-based attention (RFA) is an efficient approximation of softmax attention with linear runtime and space complexity. However, the approximation gap between RFA and con…

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