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 16511700 of 2964 papers

TitleStatusHype
What Makes Data-to-Text Generation Hard for Pretrained Language Models?0
What Makes Good Few-shot Examples for Vision-Language Models?0
What's in a Measurement? Using GPT-3 on SemEval 2021 Task 8 -- MeasEval0
When Facial Expression Recognition Meets Few-Shot Learning: A Joint and Alternate Learning Framework0
When hard negative sampling meets supervised contrastive learning0
When the Few Outweigh the Many: Illicit Content Recognition with Few-Shot Learning0
Where2Explore: Few-shot Affordance Learning for Unseen Novel Categories of Articulated Objects0
Which images to label for few-shot medical landmark detection?0
Will Multi-modal Data Improves Few-shot Learning?0
WisPerMed at BioLaySumm: Adapting Autoregressive Large Language Models for Lay Summarization of Scientific Articles0
WisPerMed at "Discharge Me!": Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on MIMIC-IV0
Wordcraft: a Human-AI Collaborative Editor for Story Writing0
xCoT: Cross-lingual Instruction Tuning for Cross-lingual Chain-of-Thought Reasoning0
Zero and Few-shot Learning for Author Profiling0
Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning0
Zero- and Few-Shot NLP with Pretrained Language Models0
Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer0
Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checking0
Zero-Shot Cross-Lingual Document-Level Event Causality Identification with Heterogeneous Graph Contrastive Transfer Learning0
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review0
Zero-Shot Learning via Class-Conditioned Deep Generative Models0
Z-Score Normalization, Hubness, and Few-Shot Learning0
Incremental Few-Shot Learning for Pedestrian Attribute Recognition0
Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach0
A Rational Model of Dimension-reduced Human Categorization0
A deep learning-enabled smart garment for accurate and versatile sleep conditions monitoring in daily life0
Granting GPT-4 License and Opportunity: Enhancing Accuracy and Confidence Estimation for Few-Shot Event Detection0
Cross-domain Named Entity Recognition via Graph Matching0
GNN-SKAN: Harnessing the Power of SwallowKAN to Advance Molecular Representation Learning with GNNs0
Effective Demonstration Annotation for In-Context Learning via Language Model-Based Determinantal Point Process0
Recent Advances in Multi-Choice Machine Reading Comprehension: A Survey on Methods and Datasets0
Evolution imposes an inductive bias that alters and accelerates learning dynamics0
FlowBERT: Prompt-tuned BERT for variable flow field prediction0
On The Impact of Merge Request Deviations on Code Review Practices0
3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve0
3D-VirtFusion: Synthetic 3D Data Augmentation through Generative Diffusion Models and Controllable Editing0
A3: Few-shot Prompt Learning of Unlearnable Examples with Cross-Modal Adversarial Feature Alignment0
A Baseline for Self-state Identification and Classification in Mental Health Data: CLPsych 2025 Task0
Accelerating Neural Self-Improvement via Bootstrapping0
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification0
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters0
A Closer Look at Prototype Classifier for Few-shot Image Classification0
A Comparative Analysis of Fine-Tuned LLMs and Few-Shot Learning of LLMs for Financial Sentiment Analysis0
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification0
A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset (MedIMeta)0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context0
A Comprehensive Overview and Survey of Recent Advances in Meta-Learning0
A Comprehensive Review of Few-shot Action Recognition0
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities0
A Contrastive Self-Supervised Learning scheme for beat tracking amenable to few-shot learning0
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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