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Few-Shot Learning

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하위 태스크: 12
평가표: 27
보존된 평가 기록: 52

Few-Shot Learning is an example of meta-learning, where a learner is trained on several related tasks, during the meta-training phase, so that it can generalize well to unseen (but related) tasks with just few examples, during the meta-testing phase. An effective approach to the Few-Shot Learning problem is to learn a common representation for various tasks and train task specific classifiers on top of this representation.

Source: Penalty Method for Inversion-Free Deep Bilevel Optimization

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/hiwonjoon/ICRA2019-Activity-Localize

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One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video

https://github.com/hkunlp/unifiedskg

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UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models

https://github.com/hl-hanlin/smkd

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Supervised Masked Knowledge Distillation for Few-Shot Transformers

https://github.com/hlings/acrofod

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AcroFOD: An Adaptive Method for Cross-domain Few-shot Object Detection

https://github.com/hologerry/AGIS-Net

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Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning

https://github.com/hongguangzhang/mlso-tmm-master

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Multi-level Second-order Few-shot Learning

https://github.com/hongyujerrywang/featureextractorstacking

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Feature Extractor Stacking for Cross-domain Few-shot Learning

https://github.com/horsepurve/deepvoro

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Few-shot Learning as Cluster-induced Voronoi Diagrams: A Geometric Approach

https://github.com/hosodakazufumi/tfdone

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It's DONE: Direct ONE-shot learning with quantile weight imprinting

https://github.com/hu-my/taskattributedistance

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Task Attribute Distance for Few-Shot Learning: Theoretical Analysis and Applications

https://github.com/huang50213/AIM-Fewshot-Continual

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Few-Shot and Continual Learning with Attentive Independent Mechanisms

https://github.com/huawei-noah/Pretrained-Language-Model

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AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models

https://github.com/huaxiuyao/GFL

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Graph Few-shot Learning via Knowledge Transfer

https://github.com/hubbs-lab-tamu/couple-stress-detection

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A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationships

https://github.com/huggingface/setfit

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Efficient Few-Shot Learning Without Prompts

https://github.com/hugofloresgarcia/music-trees

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Leveraging Hierarchical Structures for Few-Shot Musical Instrument Recognition

https://github.com/human-ai-research/hitl-few-shot-learning

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Instance Selection Mechanisms for Human-in-the-Loop Systems in Few-Shot Learning

https://github.com/humeai/competitions

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The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts

https://github.com/hurlab/vaccine-adjuvant-llm

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Cancer Vaccine Adjuvant Name Recognition from Biomedical Literature using Large Language Models

https://github.com/hushell/pmf_cvpr22

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Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference

https://github.com/hust-linyi/cat-net

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Few Shot Medical Image Segmentation with Cross Attention Transformer

https://github.com/hustvl/eva-x

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EVA-X: A Foundation Model for General Chest X-ray Analysis with Self-supervised Learning

https://github.com/hwxu20/gps

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GPS: Genetic Prompt Search for Efficient Few-shot Learning

https://github.com/hyheng/std-plm

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STD-PLM: Understanding Both Spatial and Temporal Properties of Spatial-Temporal Data with PLM

https://github.com/hytseng0509/CrossDomainFewShot

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Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation

https://github.com/iCVTEAM/CBMNet

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Cooperative Bi-path Metric for Few-shot Learning

https://github.com/iQua/CVPR2020-Shoestring

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Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data

https://github.com/ibm-granite/granite-tsfm

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Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

https://github.com/ibm/fastfit

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When LLMs are Unfit Use FastFit: Fast and Effective Text Classification with Many Classes

https://github.com/ibm/kgi-slot-filling

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Robust Retrieval Augmented Generation for Zero-shot Slot Filling

https://github.com/ibrahimself/fewtopner

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FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Framework

https://github.com/icantnamemyself/gpht

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Generative Pretrained Hierarchical Transformer for Time Series Forecasting

https://github.com/icey-zhang/diffclip

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DiffCLIP: Few-shot Language-driven Multimodal Classifier

https://github.com/icgy96/micm

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MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning

https://github.com/icvteam/dara

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Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning

https://github.com/idea-iitd/gshot

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GSHOT: Few-shot Generative Modeling of Labeled Graphs

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