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Investigating the Limitation of CLIP Models: The Worst-Performing
  Categories

Investigating the Limitation of CLIP Models: The Worst-Performing Categories

5 October 2023
Jiejing Shao
Jiang-Xin Shi
Xiao-Wen Yang
Lan-Zhe Guo
Yu-Feng Li
    VLM
ArXivPDFHTML

Papers citing "Investigating the Limitation of CLIP Models: The Worst-Performing Categories"

4 / 4 papers shown
Title
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration
Mingyang Song
Xiaoye Qu
Jiawei Zhou
Yu-Xi Cheng
VLM
59
1
0
17 Mar 2025
Evaluating Vision-Language Models as Evaluators in Path Planning
Evaluating Vision-Language Models as Evaluators in Path Planning
Mohamed Aghzal
Xiang Yue
E. Plaku
Ziyu Yao
LRM
74
1
0
27 Nov 2024
No One Left Behind: Improving the Worst Categories in Long-Tailed
  Learning
No One Left Behind: Improving the Worst Categories in Long-Tailed Learning
Yingxiao Du
Jianxin Wu
32
13
0
07 Mar 2023
Scaling Up Visual and Vision-Language Representation Learning With Noisy
  Text Supervision
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia
Yinfei Yang
Ye Xia
Yi-Ting Chen
Zarana Parekh
Hieu H. Pham
Quoc V. Le
Yun-hsuan Sung
Zhen Li
Tom Duerig
VLM
CLIP
298
3,700
0
11 Feb 2021
1