◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Jianwei Yang

4 papers hereh-index 5547 citations8 works total

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.CV3
  • cs.CL1
same name
  • Jianwei Yang — 45 papers, h 40
  • Jianwei Yang — 13 papers, h 24
  • Jianwei Yang — 9 papers, h 5
  • Jianwei Yang — 9 papers, h 7
  • Jianwei Yang — 6 papers, h 6
  • Jianwei Yang — 5 papers, h 5

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
20222024
most citedCLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks

19 citations · 27 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024★ 3 cited

Efficient Modulation for Vision Networks

Xu Ma, Xiyang Dai, Jianwei Yang +4

In this work, we present efficient modulation, a novel design for efficient vision networks. We revisit the modulation mechanism, which operates input through convolutional context…

cs.CL2023★ 1 cited

LACMA: Language-Aligning Contrastive Learning with Meta-Actions for Embodied Instruction Following

Cheng-Fu Yang, Yen-Chun Chen, Jianwei Yang +4

End-to-end Transformers have demonstrated an impressive success rate for Embodied Instruction Following when the environment has been seen in training. However, they tend to strugg…

cs.CV2023★ 4 cited

Learning from Rich Semantics and Coarse Locations for Long-tailed Object Detection

Lingchen Meng, Xiyang Dai, Jianwei Yang +7

Long-tailed object detection (LTOD) aims to handle the extreme data imbalance in real-world datasets, where many tail classes have scarce instances. One popular strategy is to expl…

cs.CV2022★ 19 cited

CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks

Zhecan Wang, Noel Codella, Yen-Chun Chen +7

Contrastive language-image pretraining (CLIP) links vision and language modalities into a unified embedding space, yielding the tremendous potential for vision-language (VL) tasks.…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.