Trending repositories for topic few-shot-learning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
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.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
A collection of AWESOME things about domian adaptation
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Python codes to implement Q-Net, a meta-learning method for few shot medical image segmentation
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
[ICLR 2022] Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Python codes to implement Q-Net, a meta-learning method for few shot medical image segmentation
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.
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
[ICLR 2022] Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A collection of AWESOME things about domian adaptation
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
A collection of AWESOME things about domian adaptation
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
Implementations of few-shot object detection benchmarks
A curated list of prompt-based paper in computer vision and vision-language learning.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
A few shot learning repository for bearing fault diagnosis.
Code release for Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
Official Code for "SingularTrajectory: Universal Trajectory Predictor using Diffusion Model (CVPR 2024)"
Official code implementation for SIGIR 23 paper Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.
Python codes to implement Q-Net, a meta-learning method for few shot medical image segmentation
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
Service to import data from various sources and index it in AI Search. Increases data relevance and reduces final size by 90%+. Useful for RAG scenarios with LLM. Hosted in Azure with serverless archi...
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Official code repository for "Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning" (published at ICLR 2023).
Log Parsing with Prompt-based Few-shot Learning (ICSE 2023, Technical Track)
Few-shot Object Counting and Detection (ECCV 2022)
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
[CVPR 2023] Glocal Energy-based Learning for Few-Shot Open-Set Recognition
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
This repository contains the implementation for the paper "Revisiting Few Shot Object Detection with Vision-Language Models"
Service to import data from various sources and index it in AI Search. Increases data relevance and reduces final size by 90%+. Useful for RAG scenarios with LLM. Hosted in Azure with serverless archi...
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
A collection of AWESOME things about domian adaptation
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
:dart: Task-oriented embedding tuning for BERT, CLIP, etc.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
[CVPR 2024] | LAMP: Learn a Motion Pattern for Few-Shot Based Video Generation
A curated list of prompt-based paper in computer vision and vision-language learning.
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
Implementations of few-shot object detection benchmarks
Official Code for "SingularTrajectory: Universal Trajectory Predictor using Diffusion Model (CVPR 2024)"
Official repo for the TMLR paper "Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language Learners"
A few shot learning repository for bearing fault diagnosis.
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
[ICLR2023] PLOT: Prompt Learning with Optimal Transport for Vision-Language Models
This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.
[CVPR-W 2023] Official Implementation of One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models
Implementation of our paper "Optimizing PatchCore for Few/many-shot Anomaly Detection"
(CVPR2023) The PyTorch implementation of the "AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domain Adaptive Object Detection".
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability (ICCV 2023)
[CVPR 2024] | LAMP: Learn a Motion Pattern for Few-Shot Based Video Generation
Few-shot Object Counting and Detection (ECCV 2022)
An index of algorithms for few-shot learning/meta-learning on graphs
The summary of code and paper for few-shot learning in fine-grained recognition