Shot Classification

Shot classification, particularly few-shot classification, focuses on training classifiers with limited labeled data, aiming to improve generalization to unseen classes. Current research emphasizes adapting pre-trained models like CLIP, employing meta-learning algorithms, and exploring techniques such as prompt engineering and hyperdimensional computing to enhance efficiency and accuracy. This field is crucial for addressing data scarcity issues in various domains, including medical imaging and natural language processing, enabling the development of more robust and adaptable AI systems.

Papers

May 22, 2023

Mitigating Catastrophic Forgetting for Few-Shot Spoken Word Classification Through Meta-Learning
Ruan van der Merwe, Herman Kamper
Natural Language Catastrophic Forgetting Meta Learning Shot Classification Continual Learning Scenario Semantic Class Speech Classification Learning Loop

May 21, 2023

Automated Few-shot Classification with Instruction-Finetuned Language Models
Rami Aly, Xingjian Shi, Kaixiang Lin, Aston Zhang, Andrew Gordon Wilson
Language Model Shot Learning Shot Classification

April 30, 2023

Few-shot Classification via Ensemble Learning with Multi-Order Statistics
Sai Yang, Fan Liu, Delong Chen, Jun Zhou
Transfer Learning Ensemble Learning Shot Classification Shot Classification Benchmark Order Statistic

April 4, 2023

Strong Baselines for Parameter Efficient Few-Shot Fine-tuning
Samyadeep Basu, Daniela Massiceti, Shell Xu Hu, Soheil Feizi
Fine Tuning Shot Classification Strong Baseline Parameter Efficient Pre Trained Vision Transformer Efficient Fine Tuning Shot Adaptation Pre Trained ViT

March 2, 2023

First-order ANIL learns linear representations despite misspecified latent dimension
Oğuz Kaan Yuksel, Etienne Boursier, Nicolas Flammarion
Reinforcement Learning Gradient Descent Shot Classification Model Agnostic Linear Representation Single Loop Latent Dimension

February 1, 2023

Stable Attribute Group Editing for Reliable Few-shot Image Generation
Guanqi Ding, Xinzhe Han, Shuhui Wang, Xin Jin, Dandan Tu, Qingming Huang
Shot Classification Shot Image Generation Attribute Editing Class Conditional Image Generation

January 28, 2023

A Closer Look at Few-shot Classification Again
Xu Luo, Hao Wu, Ji Zhang, Lianli Gao, Jing Xu, Jingkuan Song
Transfer Learning Pre Trained Model Shot Classification Glance Annotation Visual Representation Learning Training Algorithm

January 26, 2023

SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification
Pranjal Aggarwal, Ameet Deshpande, Karthik Narasimhan
Contrastive Learning Shot Classification Better Zero Product Classification Semantic Class Extreme Classification Semantic Self Supervision

January 16, 2023

Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach
Yassir Bendou, Lucas Drumetz, Vincent Gripon, Giulia Lioi, Bastien Pasdeloup
Deep Learning Shot Classification Feature Extractor Additional Disambiguation Task Shot Task

January 2, 2023

P3DC-Shot: Prior-Driven Discrete Data Calibration for Nearest-Neighbor Few-Shot Classification
Shuangmei Wang, Rui Ma, Tieru Wu, Yang Cao
Classification Code Shot Learning Nearest Neighbor Shot Classification Shot Classifier

November 29, 2022

Exploiting Category Names for Few-Shot Classification with Vision-Language Models
Taihong Xiao, Zirui Wang, Liangliang Cao, Jiahui Yu, Shengyang Dai, Ming-Hsuan Yang
Vision Language Model Classification Code Large Vision Language Model Shot Classification Vision Language Foundation Model Category Shift Shot Classification Benchmark

November 22, 2022

Knowledge Prompting for Few-shot Action Recognition
Yuheng Shi, Xinxiao Wu, Hanxi Lin
Shot Classification Shot Action Recognition Prompt Based Knowledge Action Semantics

November 16, 2022

Interpretable Few-shot Learning with Online Attribute Selection
Mohammad Reza Zarei, Majid Komeili
Shot Learning Interpretable Model Shot Classification Learned Feature Attribute Selection

November 15, 2022

MEAL: Stable and Active Learning for Few-Shot Prompting
Abdullatif Köksal, Timo Schick, Hinrich Schütze
Active Learning Shot Learning Shot Classification Shot Generalization Meal Description

November 10, 2022

Few-shot Classification with Hypersphere Modeling of Prototypes
Ning Ding, Yulin Chen, Ganqu Cui, Xiaobin Wang, Hai-Tao Zheng, Zhiyuan Liu, Pengjun Xie
Representation Learning Shot Learning Shot Classification Visual Prototype Metric Based Meta Learning

November 2, 2022

Rethinking the Metric in Few-shot Learning: From an Adaptive Multi-Distance Perspective
Jinxiang Lai, Siqian Yang, Guannan Jiang, Xi Wang, Yuxi Li, Zihui Jia, Xiaochen Chen, Jun Liu, Bin-Bin Gao, Wei Zhang, Yuan Xie, Chengjie Wang
Shot Classification North Star Metric Metric Learning Loss Shot Classifier Metric Prediction

October 19, 2022

TabLLM: Few-shot Classification of Tabular Data with Large Language Models
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David Sontag
Large Language Model Tabular Data Shot Classification Zero Shot Classification Tabular Data Classification

October 9, 2022

Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport
Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha
LeArning Abstract Optimal Transport Shot Classification Weight Matrix Adaptive Weight Distribution Calibration

September 25, 2022

Collaboration of Pre-trained Models Makes Better Few-shot Learner
Renrui Zhang, Bohao Li, Wei Zhang, Hao Dong, Hongsheng Li, Peng Gao, Yu Qiao
Pre Trained Model Contrastive Language Image Shot Classification Shot Training Shot Learner

September 5, 2022

A Study on Representation Transfer for Few-Shot Learning
Chun-Nam Yu, Yi Xie
LeArning Abstract Self Supervised Study Feature Shot Classification Feature Representation Transferable Representation