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 2951–3000 of 10307 papers

TitleStatusHype
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision—0
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality—0
A-I-RAVEN and I-RAVEN-Mesh: Two New Benchmarks for Abstract Visual Reasoning—0
DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models—0
Self-Regulated Data-Free Knowledge Amalgamation for Text Classification—0
Physics-Informed Deep Learning and Partial Transfer Learning for Bearing Fault Diagnosis in the Presence of Highly Missing Data—0
On the Effectiveness of Supervision in Asymmetric Non-Contrastive LearningCode0
ShareLoRA: Parameter Efficient and Robust Large Language Model Fine-tuning via Shared Low-Rank AdaptationCode0
A Unified View of Abstract Visual Reasoning Problems—0
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions—0
Federated Learning Optimization: A Comparative Study of Data and Model Exchange Strategies in Dynamic Networks—0
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts—0
ADSNet: Cross-Domain LTV Prediction with an Adaptive Siamese Network in Advertising—0
Augmenting Biomedical Named Entity Recognition with General-domain ResourcesCode0
A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges—0
Comparison of fine-tuning strategies for transfer learning in medical image classification—0
RASPNet: A Benchmark Dataset for Radar Adaptive Signal Processing Applications—0
UniBridge: A Unified Approach to Cross-Lingual Transfer Learning for Low-Resource LanguagesCode0
Deep Learning Models to Automate the Scoring of Hand Radiographs for Rheumatoid Arthritis—0
QMamba: On First Exploration of Vision Mamba for Image Quality AssessmentCode0
PRIBOOT: A New Data-Driven Expert for Improved Driving SimulationsCode0
Measuring training variability from stochastic optimization using robust nonparametric testing—0
Differentially Private Prototypes for Imbalanced Transfer Learning—0
Strategies for Pretraining Neural OperatorsCode0
WMAdapter: Adding WaterMark Control to Latent Diffusion Models—0
Transferring Knowledge from Large Foundation Models to Small Downstream Models—0
Advancing Roadway Sign Detection with YOLO Models and Transfer Learning—0
Large Language Models are Limited in Out-of-Context Knowledge ReasoningCode0
BertaQA: How Much Do Language Models Know About Local Culture?Code0
Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection—0
Unleashing the Power of Transfer Learning Model for Sophisticated Insect Detection: Revolutionizing Insect Classification—0
Indoor Fire and Smoke Detection Using Soft-Voting Based Deep Ensemble ModelCode0
Augmenting Offline RL with Unlabeled Data—0
SSCL-IDS: Enhancing Generalization of Intrusion Detection with Self-Supervised Contrastive LearningCode0
SecureNet: A Comparative Study of DeBERTa and Large Language Models for Phishing Detection—0
Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy—0
Contrastive learning of T cell receptor representationsCode0
A Statistical Theory of Regularization-Based Continual Learning—0
Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach—0
Utilizing Grounded SAM for self-supervised frugal camouflaged human detection—0
Concept Formation and Alignment in Language Models: Bridging Statistical Patterns in Latent Space to Concept Taxonomy—0
DeviceBERT: Applied Transfer Learning With Targeted Annotations and Vocabulary Enrichment to Identify Medical Device and Component Terminology in FDA Recall Summaries—0
Prioritizing Potential Wetland Areas via Region-to-Region Knowledge Transfer and Adaptive Propagation—0
FacLens: Transferable Probe for Foreseeing Non-Factuality in Large Language Models—0
Online Policy Distillation with Decision-Attention—0
Accelerating evolutionary exploration through language model-based transfer learning—0
Labeled Data Selection for Category Discovery—0
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch—0
Low-Resource Cross-Lingual Summarization through Few-Shot Learning with Large Language Models—0
Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models—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