few-shot-learning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc

A collection of AWESOME things about domain adaptation

总结Prompt&LLM论文，开源数据&模型，AIGC应用

Efficient few-shot learning with Sentence Transformers

FSL-Mate: A collection of resources for few-shot learning (FSL).

[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

[TPAMI 2023] LibFewShot: A Comprehensive Library for Few-shot Learning.

Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)

LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.

A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.

TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. ACM Computing Surveys, 2026.

Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)