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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/kiryteo/RG_Classification_code

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Data-Efficient Classification of Radio Galaxies

https://github.com/kjunelee/MetaOptNet

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Meta-Learning with Differentiable Convex Optimization

https://github.com/kksinghal/concept-search

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ConceptSearch: Towards Efficient Program Search Using LLMs for Abstraction and Reasoning Corpus (ARC)

https://github.com/kl4805/shoppingmmlu

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Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models

https://github.com/knoriy/CLARA

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CLARA: Multilingual Contrastive Learning for Audio Representation Acquisition

https://github.com/koava36/certrob-fewshot

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Smoothed Embeddings for Certified Few-Shot Learning

https://github.com/kojima-takeshi188/zero_shot_cot

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Large Language Models are Zero-Shot Reasoners

https://github.com/komeijiforce/cotam

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Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation

https://github.com/kuku-sichuan/ComparisonDetector

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Comparison-Based Convolutional Neural Networks for Cervical Cell/Clumps Detection in the Limited Data Scenario

https://github.com/kyxscut/CG-GAN

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Look Closer to Supervise Better: One-Shot Font Generation via Component-Based Discriminator

https://github.com/lamsoma/auto_nli

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Improving Sentence Embeddings with Automatic Generation of Training Data Using Few-shot Examples

https://github.com/laquabe/OneNet

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OneNet: A Fine-Tuning Free Framework for Few-Shot Entity Linking via Large Language Model Prompting

https://github.com/lars-research/pacia

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PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction

https://github.com/launchnlp/politics

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POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection

https://github.com/layer6ai-labs/DRESS

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DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks

https://github.com/lccc0528/stable

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StablePT: Towards Stable Prompting for Few-shot Learning via Input Separation

https://github.com/learnables/learn2learn

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learn2learn: A Library for Meta-Learning Research

https://github.com/leenamx/ge-fsod

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Generalization-Enhanced Few-Shot Object Detection in Remote Sensing

https://github.com/lehduong/poodle

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POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples

https://github.com/leileicao/protoformer

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Prototype as Query for Few Shot Semantic Segmentation

https://github.com/lenkatetkova/convexity-of-representations

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On convex decision regions in deep network representations

https://github.com/lephuoccat/TAS-few-shot

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Task Affinity with Maximum Bipartite Matching in Few-Shot Learning

https://github.com/leymir/hyperbolic-image-embeddings

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Hyperbolic Image Embeddings

https://github.com/lgnyu/vitseg

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Applying ViT in Generalized Few-shot Semantic Segmentation

https://github.com/lhtie/bio-domain-transfer

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Named Entity Recognition Under Domain Shift via Metric Learning for Life Sciences

https://github.com/liangjunfeng/srwgan

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Bias-Eliminated Semantic Refinement for Any-Shot Learning

https://github.com/likesiwell/LGM-Net

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LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning

https://github.com/lingl1024/causalfewshot

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Revisiting Few-Shot Learning from a Causal Perspective

https://github.com/linh-gist/gazeestimationtx2

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Resolving Camera Position for a Practical Application of Gaze Estimation on Edge Devices

https://github.com/linhanwang/sccnet

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Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation

https://github.com/linusericsson/ssl-transfer

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How Well Do Self-Supervised Models Transfer?

https://github.com/linzhiqiu/cross_modal_adaptation

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Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models

https://github.com/lishuo1001/ldc

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Logits DeConfusion with CLIP for Few-Shot Learning

https://github.com/lisuyi/pbadv_czsl

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Contextual Interaction via Primitive-based Adversarial Training For Compositional Zero-shot Learning

https://github.com/liulu112601/Gated-Propagation-Net

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Learning to Propagate for Graph Meta-Learning

https://github.com/liulu112601/MahiNet

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Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy

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