SOTAVerified

Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

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Showing 4101–4150 of 10307 papers

TitleStatusHype
Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification AlgorithmsCode1
Subsidiary Prototype Alignment for Universal Domain Adaptation—0
Parameter-efficient transfer learning of pre-trained Transformer models for speaker verification using adapters—0
Space-Time Graph Neural Networks with Stochastic Graph Perturbations—0
A Survey on Causal Representation Learning and Future Work for Medical Image AnalysisCode0
Joint Semantic Transfer Network for IoT Intrusion Detection—0
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems—0
Drug repositioning for Alzheimer's disease with transfer learning—0
Multi-Target Tracking with Transferable Convolutional Neural NetworksCode0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Towards High-Quality Neural TTS for Low-Resource Languages by Learning Compact Speech RepresentationsCode1
Towards automatic generation of Piping and Instrumentation Diagrams (P&IDs) with Artificial Intelligence—0
Will we run out of data? Limits of LLM scaling based on human-generated dataCode1
Knowledge Transfer For On-Device Speech Emotion Recognition with Neural Structured LearningCode0
Trade-off between reconstruction loss and feature alignment for domain generalizationCode0
Visual Answer Localization with Cross-modal Mutual Knowledge TransferCode0
Pretrained audio neural networks for Speech emotion recognition in PortugueseCode0
Multi-Environment based Meta-Learning with CSI Fingerprints for Radio Based Positioning—0
Broken Neural Scaling LawsCode1
Inducer-tuning: Connecting Prefix-tuning and Adapter-tuningCode1
Embedding neurophysiological signalsCode0
Progressive Sentiment Analysis for Code-Switched Text DataCode0
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)—0
A single-cell gene expression language modelCode1
FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural NetworksCode1
CLIP-FLow: Contrastive Learning by semi-supervised Iterative Pseudo labeling for Optical Flow Estimation—0
Accelerating Certified Robustness Training via Knowledge TransferCode0
XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic ParsingCode0
This joke is [MASK]: Recognizing Humor and Offense with Prompting—0
PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph CompletionCode1
Deep Model ReassemblyCode2
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning—0
Investigating self-supervised, weakly supervised and fully supervised training approaches for multi-domain automatic speech recognition: a study on Bangladeshi Bangla—0
Multilingual Auxiliary Tasks Training: Bridging the Gap between Languages for Zero-Shot Transfer of Hate Speech Detection ModelsCode0
Langevin dynamics based algorithm e-THO POULA for stochastic optimization problems with discontinuous stochastic gradientCode0
IT-RUDA: Information Theory Assisted Robust Unsupervised Domain Adaptation—0
Geometric Knowledge Distillation: Topology Compression for Graph Neural NetworksCode1
Neural Eigenfunctions Are Structured Representation LearnersCode1
Delving into Masked Autoencoders for Multi-Label Thorax Disease ClassificationCode1
Model ensemble instead of prompt fusion: a sample-specific knowledge transfer method for few-shot prompt tuning—0
Manifold Alignment with Label Information—0
Knowledge Transfer from Answer Ranking to Answer Generation—0
Data Augmentation for Automated Essay Scoring using Transformer Models—0
Tools for Extracting Spatio-Temporal Patterns in Meteorological Image Sequences: From Feature Engineering to Attention-Based Neural Networks—0
Probing Transfer in Deep Reinforcement Learning without Task Engineering—0
Baby Physical Safety Monitoring in Smart Home Using Action Recognition System—0
MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity RecognitionCode0
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural NetworksCode1
Real-time Detection of 2D Tool Landmarks with Synthetic Training Data—0
An Exploration of Data Efficiency in Intra-Dataset Task Transfer for Dialog Understanding—0
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified