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 501550 of 2964 papers

TitleStatusHype
Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning0
Using Multimodal Large Language Models for Automated Detection of Traffic Safety Critical Events0
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning0
VIRL: Volume-Informed Representation Learning towards Few-shot Manufacturability EstimationCode0
Mining Open Semantics from CLIP: A Relation Transition Perspective for Few-Shot Learning0
AnyTrans: Translate AnyText in the Image with Large Scale Models0
Few-Shot Recognition via Stage-Wise Retrieval-Augmented FinetuningCode1
COOL: Comprehensive Knowledge Enhanced Prompt Learning for Domain Adaptive Few-shot Fake News Detection0
RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning based on Emotional InformationCode0
Self-Supervised and Few-Shot Learning for Robust Bioaerosol Monitoring0
mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus0
Meta-Learning Neural Procedural Biases0
Bilingual Sexism Classification: Fine-Tuned XLM-RoBERTa and GPT-3.5 Few-Shot Learning0
Text2VP: Generative AI for Visual Programming and Parametric Modeling0
Anomaly Multi-classification in Industrial Scenarios: Transferring Few-shot Learning to a New TaskCode0
Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach0
MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature0
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-TrainingCode1
FlamePINN-1D: Physics-informed neural networks to solve forward and inverse problems of 1D laminar flamesCode1
Low-Resource Cross-Lingual Summarization through Few-Shot Learning with Large Language Models0
LLM-Enhanced Bayesian Optimization for Efficient Analog Layout Constraint GenerationCode1
LinkGPT: Teaching Large Language Models To Predict Missing LinksCode1
Graph Mining under Data scarcity0
LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine FeedbackCode0
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language ModelsCode2
Self-Supervised Skeleton-Based Action Representation Learning: A Benchmark and BeyondCode0
Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning0
Detecting Endangered Marine Species in Autonomous Underwater Vehicle Imagery Using Point Annotations and Few-Shot Learning0
Enhancing Trust in LLMs: Algorithms for Comparing and Interpreting LLMs0
Understanding the Cross-Domain Capabilities of Video-Based Few-Shot Action Recognition Models0
Boosting Vision-Language Models with TransductionCode2
animal2vec and MeerKAT: A self-supervised transformer for rare-event raw audio input and a large-scale reference dataset for bioacousticsCode1
Applying Fine-Tuned LLMs for Reducing Data Needs in Load Profile Analysis0
Wav2Prompt: End-to-End Speech Prompt Generation and Tuning For LLM in Zero and Few-shot Learning0
Large Language Models: A New Approach for Privacy Policy Analysis at Scale0
Multimodal Cross-Domain Few-Shot Learning for Egocentric Action Recognition0
Few-shot fault diagnosis based on multi-scale graph convolution filtering for industry0
On the Limits of Multi-modal Meta-Learning with Auxiliary Task Modulation Using Conditional Batch Normalization0
Learning Human-Aligned Representations with Contrastive Learning and Generative Similarity0
Mashee at SemEval-2024 Task 8: The Impact of Samples Quality on the Performance of In-Context Learning for Machine Text Classification0
Low-Rank Few-Shot Adaptation of Vision-Language ModelsCode3
RAGSys: Item-Cold-Start Recommender as RAG System0
On Understanding Attention-Based In-Context Learning for Categorical Data0
THREAD: Thinking Deeper with Recursive SpawningCode1
Exploring the LLM Journey from Cognition to Expression with Linear Representations0
TEII: Think, Explain, Interact and Iterate with Large Language Models to Solve Cross-lingual Emotion DetectionCode0
Compressing Lengthy Context With UltraGistCode1
Magnetic Resonance Image Processing Transformer for General Accelerated Image Reconstruction0
AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2Code2
What Makes Good Few-shot Examples for Vision-Language Models?0
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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