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

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Showing 876–900 of 2964 papers

Title	Date	Tasks	Status
Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks	Aug 31, 2022	Deep LearningFew-Shot Learning	—Unverified
Explicit Knowledge Transfer for Weakly-Supervised Code Generation	Nov 30, 2022	Code GenerationFew-Shot Learning	—Unverified
CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems	Sep 10, 2021	dialog state trackingFew-Shot Learning	—Unverified
Catalysis distillation neural network for the few shot open catalyst challenge	May 31, 2023	Computational chemistryFew-Shot Learning	—Unverified
Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning	Jan 19, 2023	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Enhancing Trust in LLMs: Algorithms for Comparing and Interpreting LLMs	Jun 4, 2024	BenchmarkingFairness	—Unverified
Exploiting the Potential of Seq2Seq Models as Robust Few-Shot Learners	Jul 27, 2023	DecoderFew-Shot Learning	—Unverified
Explore the Power of Dropout on Few-shot Learning	Jan 26, 2023	Deep LearningFew-Shot Image Classification	—Unverified
Active Object Manipulation Facilitates Visual Object Learning: An Egocentric Vision Study	Jun 4, 2019	Few-Shot LearningObject	—Unverified
AdaDurIAN: Few-shot Adaptation for Neural Text-to-Speech with DurIAN	May 12, 2020	Few-Shot Learningtext-to-speech	—Unverified
Exploring Data Augmentation Methods on Social Media Corpora	Mar 3, 2023	Data AugmentationFew-Shot Learning	—Unverified
Few-shot Learning for Cross-Target Stance Detection by Aggregating Multimodal Embeddings	Jan 11, 2023	Few-Shot LearningStance Detection	—Unverified
Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot learning	Feb 3, 2024	Few-Shot LearningLearning-To-Rank	—Unverified
Exploring Factual Entailment with NLI: A News Media Study	Jun 24, 2024	ArticlesFew-Shot Learning	—Unverified
Enhancing TCR-Peptide Interaction Prediction with Pretrained Language Models and Molecular Representations	Apr 22, 2025	BenchmarkingFew-Shot Learning	—Unverified
Exploring Generative AI Techniques in Government: A Case Study	Apr 6, 2025	Few-Shot LearningManagement	—Unverified
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study	Nov 21, 2023	Data AugmentationFew-Shot Learning	—Unverified
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?	Oct 10, 2024	Few-Shot LearningIn-Context Learning	—Unverified
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning	Feb 6, 2024	Few-Shot Learningimage-classification	—Unverified
Enhancing Prototypical Few-Shot Learning by Leveraging the Local-Level Strategy	Nov 8, 2021	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Exploring representation learning for flexible few-shot tasks	Jan 1, 2021	Few-Shot LearningRepresentation Learning	—Unverified
Class Interference Regularization	Sep 4, 2020	Face VerificationFew-Shot Learning	—Unverified
Exploring Sentiment Dynamics and Predictive Behaviors in Cryptocurrency Discussions by Few-Shot Learning with Large Language Models	Sep 4, 2024	Decision MakingFew-Shot Learning	—Unverified
Enhancing News Summarization with ELearnFit through Efficient In-Context Learning and Efficient Fine-Tuning	May 4, 2024	ArticlesFew-Shot Learning	—Unverified
Can LLMs Assist Annotators in Identifying Morality Frames? -- Case Study on Vaccination Debate on Social Media	Feb 4, 2025	Few-Shot Learning	—Unverified

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All datasets MedConceptsQA DTD FGVC-Aircraft Mini-ImageNet - 5-Shot Learning Mini-Imagenet 5-way (1-shot)Stanford Cars Mini-ImageNet - 1-Shot Learning PubMedQA Caltech101 CaseHOLD EuroSAT Flowers-102

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	gpt-4-0125-preview	Accuracy	61.91	—	Unverified
2	gpt-4-0125-preview	Accuracy	52.49	—	Unverified
3	gpt-3.5-turbo	Accuracy	41.48	—	Unverified
4	gpt-3.5-turbo	Accuracy	37.06	—	Unverified
5	johnsnowlabs/JSL-MedMNX-7B	Accuracy	25.63	—	Unverified
6	yikuan8/Clinical-Longformer	Accuracy	25.55	—	Unverified
7	BioMistral/BioMistral-7B-DARE	Accuracy	25.06	—	Unverified
8	yikuan8/Clinical-Longformer	Accuracy	25.04	—	Unverified
9	PharMolix/BioMedGPT-LM-7B	Accuracy	24.92	—	Unverified
10	PharMolix/BioMedGPT-LM-7B	Accuracy	24.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	67.27	—	Unverified
2	SaSPA + CAL	4-shot Accuracy	48.3	—	Unverified
3	Real-Guidance + CAL	4-shot Accuracy	41.5	—	Unverified
4	CAL	4-shot Accuracy	40.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SaSPA + CAL	Harmonic mean	52.2	—	Unverified
2	CAL	Harmonic mean	35.2	—	Unverified
3	Variational Prompt Tuning	Harmonic mean	34.69	—	Unverified
4	Real-Guidance + CAL	Harmonic mean	34.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BGNN	Accuracy	92.7	—	Unverified
2	TIM-GD	Accuracy	87.4	—	Unverified
3	UNEM-Gaussian	Accuracy	66.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EASY (transductive)	Accuracy	82.75	—	Unverified
2	HCTransformers	5 way 1~2 shot	74.74	—	Unverified
3	HyperShot	Accuracy	53.18	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SaSPA + CAL	4-shot Accuracy	66.7	—	Unverified
2	Real-Guidance + CAL	4-shot Accuracy	44.3	—	Unverified
3	CAL	4-shot Accuracy	42.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HCTransformers	Acc	74.74	—	Unverified
2	DPGN	Acc	67.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MetaGen Blended RAG (zero-shot)	Accuracy	77.9	—	Unverified
2	CoT-T5-11B (1024 Shot)	Accuracy	73.42	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	96.44	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CoT-T5-11B (1024 Shot)	Accuracy	68.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	77.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	81.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	91.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CovidExpert	AUC-ROC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CoT-T5-11B (1024 Shot)	Accuracy	78.02	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UNEM-Gaussian	Accuracy	65.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UNEM-Gaussian	Accuracy	73.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	96.82	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	73.07	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	78.51	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UNEM-Gaussian	Accuracy	52.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	79	—	Unverified