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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1926–1950 of 2964 papers

Title	Date	Tasks	Status
CANAL -- Cyber Activity News Alerting Language Model: Empirical Approach vs. Expensive LLM	May 10, 2024	ArticlesFew-Shot Learning	—Unverified
CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models	Apr 18, 2023	Few-Shot LearningPrediction	—Unverified
Can Explanations Be Useful for Calibrating Black Box Models?	Nov 16, 2021	Extractive Question-AnsweringFew-Shot Learning	—Unverified
Can Foundation Models Really Segment Tumors? A Benchmarking Odyssey in Lung CT Imaging	May 2, 2025	BenchmarkingComputational Efficiency	—Unverified
Can GPT tell us why these images are synthesized? Empowering Multimodal Large Language Models for Forensics	Apr 16, 2025	Few-Shot LearningImage Manipulation	—Unverified
Can LLMs Assist Annotators in Identifying Morality Frames? -- Case Study on Vaccination Debate on Social Media	Feb 4, 2025	Few-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
Catalysis distillation neural network for the few shot open catalyst challenge	May 31, 2023	Computational chemistryFew-Shot Learning	—Unverified
Causal Interventions-based Few-Shot Named Entity Recognition	May 3, 2023	Few-Shot Learningfew-shot-ner	—Unverified
CellularLint: A Systematic Approach to Identify Inconsistent Behavior in Cellular Network Specifications	Jul 18, 2024	Few-Shot Learning	—Unverified
Centroid-based deep metric learning for speaker recognition	Feb 6, 2019	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Chain-of-Thought Textual Reasoning for Few-shot Temporal Action Localization	Apr 18, 2025	Action LocalizationAnomaly Detection	—Unverified
Channel Phase Processing in Wireless Networks for Human Activity Recognition	Mar 29, 2023	Activity RecognitionDenoising	—Unverified
Channel-Spatial-Based Few-Shot Bird Sound Event Detection	Jun 18, 2023	Event DetectionFew-Shot Learning	—Unverified
ChatGPT and general-purpose AI count fruits in pictures surprisingly well	Apr 12, 2024	Deep LearningFew-Shot Learning	—Unverified
ChatGPT for Arabic Grammatical Error Correction	Aug 8, 2023	Few-Shot LearningGrammatical Error Correction	—Unverified
Check-worthy Claim Detection across Topics for Automated Fact-checking	Dec 16, 2022	Data AugmentationFact Checking	—Unverified
CINS: Comprehensive Instruction for Few-shot Learning in Task-oriented Dialog Systems	Sep 10, 2021	dialog state trackingFew-Shot Learning	—Unverified
Circumpapillary OCT-Focused Hybrid Learning for Glaucoma Grading Using Tailored Prototypical Neural Networks	Jun 25, 2021	Few-Shot Learning	—Unverified
Class Imbalance in Few-Shot Learning	Jan 1, 2021	Few-Shot Learning	—Unverified
Class-Incremental Few-Shot Event Detection	Apr 2, 2024	Event DetectionFew-Shot Learning	—Unverified
Class Interference Regularization	Sep 4, 2020	Face VerificationFew-Shot Learning	—Unverified
Class-Specific Channel Attention for Few-Shot Learning	Sep 3, 2022	Few-Shot Classification and SegmentationFew-Shot Image Classification	—Unverified
CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion	Feb 22, 2024	Contrastive LearningFew-Shot Learning	—Unverified
CLEAN-EVAL: Clean Evaluation on Contaminated Large Language Models	Nov 15, 2023	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