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
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.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
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.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
Implementations of few-shot object detection benchmarks
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
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.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
Implementations of few-shot object detection benchmarks
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
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 domian adaptation
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
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.
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.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose ...
A few shot learning repository for bearing fault diagnosis.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose ...
A few shot learning repository for bearing fault diagnosis.
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
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
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
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
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
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
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.
A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
Implementations of few-shot object detection benchmarks
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.
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
A few shot learning repository for bearing fault diagnosis.
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).
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability (ICCV 2023)
[ICLR 2023] The official code for our ICLR 2023 (top25%) paper: "Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning"
The summary of code and paper for few-shot learning in fine-grained recognition
[ICRA2024] Few-Shot Panoptic Segmentation With Foundation Models
Official Code for "SingularTrajectory: Universal Trajectory Predictor using Diffusion Model (CVPR 2024)"
[ICLR2023] PLOT: Prompt Learning with Optimal Transport for Vision-Language Models
This repository is the official implementation Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.
A set of utilities for running few-shot prompting experiments on large-language models
Hands-On Deep Learning Algorithms with Python, By Packt
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
Official Code for "SingularTrajectory: Universal Trajectory Predictor using Diffusion Model (CVPR 2024)"
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
Official repo for the TMLR paper "Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language Learners"
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.
:dart: Task-oriented embedding tuning for BERT, CLIP, etc.
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
[CVPR 2024] | LAMP: Learn a Motion Pattern for Few-Shot Based Video Generation
LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023.
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
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 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
Implementations of few-shot object detection benchmarks
Official Code for "SingularTrajectory: Universal Trajectory Predictor using Diffusion Model (CVPR 2024)"
[CVPR 2024] | LAMP: Learn a Motion Pattern for Few-Shot Based Video Generation
Mixing Language Models with Self-Verification and Meta-Verification
A few shot learning repository for bearing fault diagnosis.
(CVPR2023) The PyTorch implementation of the "AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domain Adaptive Object Detection".
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
[ECCV 2024] - Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
CVPR 2023: Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification
Code release for Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning
[ICRA2024] Few-Shot Panoptic Segmentation With Foundation Models
Implementation of our paper "Optimizing PatchCore for Few/many-shot Anomaly Detection"
[CVPR-W 2023] Official Implementation of One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models
[ICLR2023] PLOT: Prompt Learning with Optimal Transport for Vision-Language Models
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability (ICCV 2023)
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc