Text Descriptions are Compressive and Invariant Representations for
Visual Learning

Text Descriptions are Compressive and Invariant Representations for Visual Learning

10 July 2023

J. Zico Kolter

Papers citing "Text Descriptions are Compressive and Invariant Representations for Visual Learning"

8 / 8 papers shown

Title
Does VLM Classification Benefit from LLM Description Semantics? Pingchuan Ma Lennart Rietdorf Dmytro Kotovenko Vincent Tao Hu Bjorn Ommer VLM 67 0 0 16 Dec 2024
Storyboard guided Alignment for Fine-grained Video Action Recognition Enqi Liu Liyuan Pan Yan Yang Yiran Zhong Zhijing Wu Xinxiao Wu Liu Liu 28 0 0 18 Oct 2024
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and Transparency Maor Dikter Tsachi Blau Chaim Baskin 33 0 0 13 Jun 2024
If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions Reza Esfandiarpoor Cristina Menghini Stephen H. Bach CoGe VLM 27 8 0 25 Mar 2024
Spurious Feature Diversification Improves Out-of-distribution Generalization Yong Lin Lu Tan Yifan Hao Honam Wong Hanze Dong Weizhong Zhang Yujiu Yang Tong Zhang OODD 6 24 0 29 Sep 2023
What does a platypus look like? Generating customized prompts for zero-shot image classification Sarah M Pratt Ian Covert Rosanne Liu Ali Farhadi VLM 119 212 0 07 Sep 2022
Prompt-aligned Gradient for Prompt Tuning Beier Zhu Yulei Niu Yucheng Han Yuehua Wu Hanwang Zhang VLM 175 269 0 30 May 2022
Learning to Prompt for Vision-Language Models Kaiyang Zhou Jingkang Yang Chen Change Loy Ziwei Liu VPVLM CLIP VLM 322 2,249 0 02 Sep 2021