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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/16337093/PnP-FSOD

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Instant Response Few-shot Object Detection with Meta Strategy and Explicit Localization Inference

https://github.com/1KE-JI/HierVerb

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Hierarchical Verbalizer for Few-Shot Hierarchical Text Classification

https://github.com/1adrianb/lasp

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LASP: Text-to-Text Optimization for Language-Aware Soft Prompting of Vision & Language Models

https://github.com/1adrianb/unsupervised-face-representation

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Pre-training strategies and datasets for facial representation learning

https://github.com/231sm/Low_Resource_KBP

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Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection

https://github.com/3DAgentWorld/Toolkit-for-Prompt-Compression

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PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language Models

https://github.com/3dperceptionlab/toad

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Text-driven Online Action Detection

https://github.com/772922440/pgada

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PGADA: Perturbation-Guided Adversarial Alignment for Few-shot Learning Under the Support-Query Shift

https://github.com/AI-secure/Meta-Neural-Kernel

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Global Convergence and Generalization Bound of Gradient-Based Meta-Learning with Deep Neural Nets

https://github.com/AIVResearch/MSANet

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MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation

https://github.com/AKC23/Harnessing-LLMs-over-transformer-models-for-detecting-Bengali-depressive-text-A-comprehensive-study

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Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive Study

https://github.com/ANDYZAQ/GF-SAM

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Bridge the Points: Graph-based Few-shot Segment Anything Semantically

https://github.com/AceChuse/TaskLevelAug

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Task Augmentation by Rotating for Meta-Learning

https://github.com/AhmedFrikha/Few-Shot-One-Class-Classification-via-Meta-Learning

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Few-Shot One-Class Classification via Meta-Learning

https://github.com/Alejandro-Galan/Few-shot_COVID-19_Inter-vs-Intra

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Few-shot learning for COVID-19 Chest X-Ray Classification with Imbalanced Data: An Inter vs. Intra Domain Study

https://github.com/Alibaba-AAIG/SSL-FEW-SHOT

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Self-Supervised Learning For Few-Shot Image Classification

https://github.com/Alibaba-NLP/ProtoRE

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Prototypical Representation Learning for Relation Extraction

https://github.com/AlibabaPAI/one_shot_text_labeling

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One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction

https://github.com/Amgao/RLS-RTMDNet

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Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking

https://github.com/AmmarKamoona/RFS-Energy-Anomaly-Detection-of-Defect

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Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework

https://github.com/Ant-Brain/EfficientWord-Net

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EfficientWord-Net: An Open Source Hotword Detection Engine based on One-shot Learning

https://github.com/AntreasAntoniou/FewShotContinualLearning

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Defining Benchmarks for Continual Few-Shot Learning

https://github.com/ArchitParnami/Few-Shot-Privacy

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Privacy Enhancement for Cloud-Based Few-Shot Learning

https://github.com/ArnoutDevos/RegressionNet

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Regression Networks for Meta-Learning Few-Shot Classification

https://github.com/AtmaHou/FewShotTagging

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Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network

https://github.com/AtmaHou/MetaDialog

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FewJoint: A Few-shot Learning Benchmark for Joint Language Understanding

https://github.com/AutodeskAILab/UVStyle-Net

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UVStyle-Net: Unsupervised Few-shot Learning of 3D Style Similarity Measure for B-Reps

https://github.com/AuvaLab/itext2kg

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iText2KG: Incremental Knowledge Graphs Construction Using Large Language Models

https://github.com/AyanKumarBhunia/Deep-One-Shot-Logo-Retrieval

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A Deep One-Shot Network for Query-based Logo Retrieval

https://github.com/Babakbehkamkia/GPT-Stance-Detection

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Zero-Shot Stance Detection using Contextual Data Generation with LLMs

https://github.com/BaiShuanghao/CDFSC-MLP

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Improving Cross-domain Few-shot Classification with Multilayer Perceptron

https://github.com/BatsResearch/efsl

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Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks

https://github.com/BayesWatch/deep-kernel-transfer

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Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels

https://github.com/BeautyOfWeb/AffinityNet

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AffinityNet: semi-supervised few-shot learning for disease type prediction

https://github.com/Bibkiller/ASR

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Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation

https://github.com/BinahHu/ADE-FewShot

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Unlocking the Full Potential of Small Data with Diverse Supervision

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