SOTAVerified

Few-Shot Learning

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

Papers

Showing 14011450 of 2964 papers

TitleStatusHype
All You Need in Knowledge Distillation Is a Tailored Coordinate System0
Differentiable Entailment for Parameter Efficient Few Shot Learning0
A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset (MedIMeta)0
From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems0
Hyperspectral Imaging-Based Grain Quality Assessment With Limited Labelled Data0
Hyperspherical embedding for novel class classification0
CryoMAE: Few-Shot Cryo-EM Particle Picking with Masked Autoencoders0
From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models0
Crowdsourcing with Meta-Workers: A New Way to Save the Budget0
I Can Find You in Seconds! Leveraging Large Language Models for Code Authorship Attribution0
Automatic detection of rare pathologies in fundus photographs using few-shot learning0
ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)0
From Dataset to Real-world: General 3D Object Detection via Generalized Cross-domain Few-shot Learning0
Identifying Fairness Issues in Automatically Generated Testing Content0
Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation0
Identity Document to Selfie Face Matching Across Adolescence0
FrLove : Could a Frenchman rapidly identify Lovecraft?0
Few-shot Medical Image Segmentation via Cross-Reference Transformer0
Cross-Modulation Networks for Few-Shot Learning0
iFuzzyTL: Interpretable Fuzzy Transfer Learning for SSVEP BCI System0
Frequency Guidance Matters in Few-Shot Learning0
Automatic Combination of Sample Selection Strategies for Few-Shot Learning0
ALLSH: Active Learning Guided by Local Sensitivity and Hardness0
It's About Time: Incorporating Temporality in Retrieval Augmented Language Models0
IMG2IMU: Translating Knowledge from Large-Scale Images to IMU Sensing Applications0
IUP: An Intelligent Utility Prediction Scheme for Solid-State Fermentation in 5G IoT0
Impact of Aliasing on Generalization in Deep Convolutional Networks0
Impossible Triangle: What's Next for Pre-trained Language Models?0
Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control0
Improved Few-Shot Visual Classification0
Cross-Modal Mapping: Mitigating the Modality Gap for Few-Shot Image Classification0
Improvement Strategies for Few-Shot Learning in OCT Image Classification of Rare Retinal Diseases0
Cross-Modal Learning for Chemistry Property Prediction: Large Language Models Meet Graph Machine Learning0
Four Eyes Are Better Than Two: Harnessing the Collaborative Potential of Large Models via Differentiated Thinking and Complementary Ensembles0
Automate Knowledge Concept Tagging on Math Questions with LLMs0
Automated Human Cell Classification in Sparse Datasets using Few-Shot Learning0
FORML: A Riemannian Hessian-free Method for Meta-learning on Stiefel Manifolds0
FontTransformer: Few-shot High-resolution Chinese Glyph Image Synthesis via Stacked Transformers0
cross-modal knowledge enhancement mechanism for few-shot learning0
FoMo: A Foundation Model for Mobile Traffic Forecasting with Diffusion Model0
Improving Few-Shot Learning using Composite Rotation based Auxiliary Task0
Cross-Modality Multi-Atlas Segmentation Using Deep Neural Networks0
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning0
Improving Few-Shot Performance of Language Models via Nearest Neighbor Calibration0
Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations0
Enhancing Few-Shot Image Classification with Unlabelled Examples0
Improving Few-Shot Visual Classification with Unlabelled Examples0
Distributed Rule Vectors is A Key Mechanism in Large Language Models' In-Context Learning0
Distributionally Robust Weighted k-Nearest Neighbors0
Cross-Modal Few-Shot Learning: a Generative Transfer Learning Framework0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1gpt-4-0125-previewAccuracy61.91Unverified
2gpt-4-0125-previewAccuracy52.49Unverified
3gpt-3.5-turboAccuracy41.48Unverified
4gpt-3.5-turboAccuracy37.06Unverified
5johnsnowlabs/JSL-MedMNX-7BAccuracy25.63Unverified
6yikuan8/Clinical-LongformerAccuracy25.55Unverified
7BioMistral/BioMistral-7B-DAREAccuracy25.06Unverified
8yikuan8/Clinical-LongformerAccuracy25.04Unverified
9PharMolix/BioMedGPT-LM-7BAccuracy24.92Unverified
10PharMolix/BioMedGPT-LM-7BAccuracy24.75Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean67.27Unverified
2SaSPA + CAL4-shot Accuracy48.3Unverified
3Real-Guidance + CAL4-shot Accuracy41.5Unverified
4CAL4-shot Accuracy40.9Unverified
#ModelMetricClaimedVerifiedStatus
1SaSPA + CALHarmonic mean52.2Unverified
2CALHarmonic mean35.2Unverified
3Variational Prompt TuningHarmonic mean34.69Unverified
4Real-Guidance + CALHarmonic mean34.5Unverified
#ModelMetricClaimedVerifiedStatus
1BGNNAccuracy92.7Unverified
2TIM-GDAccuracy87.4Unverified
3UNEM-GaussianAccuracy66.4Unverified
#ModelMetricClaimedVerifiedStatus
1EASY (transductive)Accuracy82.75Unverified
2HCTransformers5 way 1~2 shot74.74Unverified
3HyperShotAccuracy53.18Unverified
#ModelMetricClaimedVerifiedStatus
1SaSPA + CAL4-shot Accuracy66.7Unverified
2Real-Guidance + CAL4-shot Accuracy44.3Unverified
3CAL4-shot Accuracy42.2Unverified
#ModelMetricClaimedVerifiedStatus
1HCTransformersAcc74.74Unverified
2DPGNAcc67.6Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAG (zero-shot)Accuracy77.9Unverified
2CoT-T5-11B (1024 Shot)Accuracy73.42Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean96.44Unverified
#ModelMetricClaimedVerifiedStatus
1CoT-T5-11B (1024 Shot)Accuracy68.3Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean77.71Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean81.12Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean91.57Unverified
#ModelMetricClaimedVerifiedStatus
1CovidExpertAUC-ROC1Unverified
#ModelMetricClaimedVerifiedStatus
1CoT-T5-11B (1024 Shot)Accuracy78.02Unverified
#ModelMetricClaimedVerifiedStatus
1UNEM-GaussianAccuracy65.7Unverified
#ModelMetricClaimedVerifiedStatus
1UNEM-GaussianAccuracy73.2Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean96.82Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean73.07Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean78.51Unverified
#ModelMetricClaimedVerifiedStatus
1UNEM-GaussianAccuracy52.3Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean79Unverified