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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/mohammedsb/dinov2forradiology

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Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks

https://github.com/mohna0310/zssc

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Zero-shot Approach to Overcome Perturbation Sensitivity of Prompts

https://github.com/moonsh/hm-hybrid-masking

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HM: Hybrid Masking for Few-Shot Segmentation

https://github.com/moonsh/msi-maximize-support-set-information

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MSI: Maximize Support-Set Information for Few-Shot Segmentation

https://github.com/moukamisama/f2m

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Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima

https://github.com/movinghoon/ESFR

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Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification

https://github.com/mpatacchiola/contextual-squeeze-and-excitation

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Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification

https://github.com/mpatacchiola/imujoco

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Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation

https://github.com/mprompting/xlmrprompt

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Discrete and Soft Prompting for Multilingual Models

https://github.com/mrkshllr/FewTURE

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Rethinking Generalization in Few-Shot Classification

https://github.com/mrusci/ondevice-fewshot-kws

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Few-Shot Open-Set Learning for On-Device Customization of KeyWord Spotting Systems

https://github.com/muraliadithya/vdp

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Composing Neural Learning and Symbolic Reasoning with an Application to Visual Discrimination

https://github.com/mustafa1728/wlsegnet

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A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation

https://github.com/mxhofer/Named-Entity-Recognition-BidirectionalLSTM-CNN-CoNLL

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Few-shot Learning for Named Entity Recognition in Medical Text

https://github.com/myhakureimu/prerec

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Pre-trained Recommender Systems: A Causal Debiasing Perspective

https://github.com/nadavlab/MedConceptsQA

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MedConceptsQA: Open Source Medical Concepts QA Benchmark

https://github.com/naeem-paeedeh/adapter

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Cross-Domain Few-Shot Learning via Adaptive Transformer Networks

https://github.com/naiveneuron/wikigoldsk

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WikiGoldSK: Annotated Dataset, Baselines and Few-Shot Learning Experiments for Slovak Named Entity Recognition

https://github.com/namednil/sip

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SIP: Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation

https://github.com/namednil/step

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Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations

https://github.com/namespace-pt/ultragist

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Compressing Lengthy Context With UltraGist

https://github.com/nathanielsimard/improving-fs-ssl

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Improving Few-Shot Learning with Auxiliary Self-Supervised Pretext Tasks

https://github.com/naver-ai/carecall-corpus

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Building a Role Specified Open-Domain Dialogue System Leveraging Large-Scale Language Models

https://github.com/naver/biobert-pretrained

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BioBERT: a pre-trained biomedical language representation model for biomedical text mining

https://github.com/nayeemrizve/invariance-equivariance

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Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning

https://github.com/neuraloperator/coda-no

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Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs

https://github.com/ngandh/F2LCough

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Federated Few-shot Learning for Cough Classification with Edge Devices

https://github.com/ngl567/GANA-FewShotKGC

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Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion

https://github.com/nhhoang96/Semantic_Matching

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Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection

https://github.com/nicolas-lair/AidMe

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User-in-the-loop Adaptive Intent Detection for Instructable Digital Assistant

https://github.com/nicpopovic/fredo

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Few-Shot Document-Level Relation Extraction

https://github.com/niejiahao1998/ifa

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Cross-Domain Few-Shot Segmentation via Iterative Support-Query Correspondence Mining

https://github.com/nielsschluesener/fast-learning-hand-gesture-recognition

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Fast Learning of Dynamic Hand Gesture Recognition with Few-Shot Learning Models

https://github.com/nii-yamagishilab/ssl_vits_df

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Exploring Self-Supervised Vision Transformers for Deepfake Detection: A Comparative Analysis

https://github.com/nitaytech/domainrobustness

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Measuring the Robustness of NLP Models to Domain Shifts

https://github.com/nitaytech/domainrobustnessdata

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Measuring the Robustness of NLP Models to Domain Shifts

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