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 76–100 of 2964 papers

Title	Date	Tasks	Status	Hype
Logits DeConfusion with CLIP for Few-Shot Learning	Apr 16, 2025	Few-Shot Learning	CodeCode Available	2
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency	Apr 16, 2025	Few-Shot LearningInteractive Segmentation	CodeCode Available	1
Improving Instruct Models for Free: A Study on Partial Adaptation	Apr 15, 2025	Few-Shot LearningIn-Context Learning	—Unverified	0
TSAL: Few-shot Text Segmentation Based on Attribute Learning	Apr 15, 2025	AttributeFew-Shot Learning	—Unverified	0
AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification	Apr 14, 2025	Contrastive LearningFew-Shot Learning	—Unverified	0
Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving	Apr 14, 2025	Autonomous DrivingBrain Computer Interface	—Unverified	0
Investigating Vision-Language Model for Point Cloud-based Vehicle Classification	Apr 10, 2025	Autonomous DrivingClassification	—Unverified	0
MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning	Apr 9, 2025	Anomaly DetectionAnomaly Segmentation	—Unverified	0
A Cross-Domain Few-Shot Learning Method Based on Domain Knowledge Mapping	Apr 9, 2025	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified	0
Few-Shot Adaptation of Grounding DINO for Agricultural Domain	Apr 9, 2025	Few-Shot Learningobject-detection	—Unverified	0
Mind the Gap: Evaluating Vision Systems in Small Data Applications	Apr 8, 2025	Few-Shot Learning	CodeCode Available	0
AI for Climate Finance: Agentic Retrieval and Multi-Step Reasoning for Early Warning System Investments	Apr 7, 2025	Few-Shot LearningRAG	—Unverified	0
Enhancing NER Performance in Low-Resource Pakistani Languages using Cross-Lingual Data Augmentation	Apr 7, 2025	Data AugmentationFew-Shot Learning	—Unverified	0
Exploring Generative AI Techniques in Government: A Case Study	Apr 6, 2025	Few-Shot LearningManagement	—Unverified	0
Exploring the Capabilities of LLMs for IMU-based Fine-grained Human Activity Understanding	Apr 2, 2025	Activity RecognitionFew-Shot Learning	—Unverified	0
CoRAG: Collaborative Retrieval-Augmented Generation	Apr 2, 2025	Few-Shot LearningOpen-Domain Question Answering	—Unverified	0
Is Temporal Prompting All We Need For Limited Labeled Action Recognition?	Apr 2, 2025	Action RecognitionAll	—Unverified	0
Synthesized Annotation Guidelines are Knowledge-Lite Boosters for Clinical Information Extraction	Apr 1, 2025	Few-Shot Learningnamed-entity-recognition	—Unverified	0
Hierarchical Local-Global Feature Learning for Few-shot Malicious Traffic Detection	Apr 1, 2025	Few-Shot LearningTraffic Classification	—Unverified	0
AI-Assisted Colonoscopy: Polyp Detection and Segmentation using Foundation Models	Mar 31, 2025	Few-Shot Learning	CodeCode Available	0
Texture or Semantics? Vision-Language Models Get Lost in Font Recognition	Mar 31, 2025	Few-Shot LearningFont Recognition	CodeCode Available	0
Large Language Models are Unreliable for Cyber Threat Intelligence	Mar 29, 2025	Few-Shot LearningZero-Shot Learning	—Unverified	0
Unbiased Max-Min Embedding Classification for Transductive Few-Shot Learning: Clustering and Classification Are All You Need	Mar 28, 2025	AllClassification	—Unverified	0
Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data	Mar 27, 2025	Few-Shot LearningMeta-Learning	—Unverified	0
From User Preferences to Optimization Constraints Using Large Language Models	Mar 27, 2025	Few-Shot Learning	—Unverified	0

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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