Improving Few-Shot Image Classification Using Machine- and User-Generated Natural Language Descriptions

7 July 2022

Papers citing "Improving Few-Shot Image Classification Using Machine- and User-Generated Natural Language Descriptions"

8 / 8 papers shown

Title
Model-agnostic Coreset Selection via LLM-based Concept Bottlenecks Akshay Mehra Trisha Mittal Subhadra Gopalakrishnan Joshua Kimball 45 0 0 23 Feb 2025
Explanation Bottleneck Models Shinýa Yamaguchi Kosuke Nishida LRM BDL 51 1 0 26 Sep 2024
GazeXplain: Learning to Predict Natural Language Explanations of Visual Scanpaths Xianyu Chen Ming Jiang Qi Zhao 24 2 0 05 Aug 2024
Reading Is Believing: Revisiting Language Bottleneck Models for Image Classification Honori Udo Takafumi Koshinaka VLM 43 0 0 22 Jun 2024
LLM-based Hierarchical Concept Decomposition for Interpretable Fine-Grained Image Classification Renyi Qu Mark Yatskar 26 1 0 29 May 2024
Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification Yue Yang Artemis Panagopoulou Shenghao Zhou Daniel Jin Chris Callison-Burch Mark Yatskar 40 213 0 21 Nov 2022
What you can cram into a single vector: Probing sentence embeddings for linguistic properties Alexis Conneau Germán Kruszewski Guillaume Lample Loïc Barrault Marco Baroni 201 882 0 03 May 2018
Learning Deep Representations of Fine-grained Visual Descriptions Scott E. Reed Zeynep Akata Bernt Schiele Honglak Lee OCL VLM 170 840 0 17 May 2016