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 2651–2700 of 10307 papers

TitleStatusHype
Prototype-based HyperAdapter for Sample-Efficient Multi-task TuningCode0
Relearning Forgotten Knowledge: on Forgetting, Overfit and Training-Free Ensembles of DNNs—0
Unlocking Emergent Modularity in Large Language ModelsCode1
Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric PerspectiveCode1
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning—0
DemoSG: Demonstration-enhanced Schema-guided Generation for Low-resource Event Extraction—0
Structural transfer learning of non-Gaussian DAG—0
UNO-DST: Leveraging Unlabelled Data in Zero-Shot Dialogue State TrackingCode0
Interpreting and Exploiting Functional Specialization in Multi-Head Attention under Multi-task LearningCode0
Class-Specific Data Augmentation: Bridging the Imbalance in Multiclass Breast Cancer Classification—0
Lifelong Sequence Generation with Dynamic Module Expansion and Adaptation—0
Empirical study of pretrained multilingual language models for zero-shot cross-lingual knowledge transfer in generation—0
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
Sub-network Discovery and Soft-masking for Continual Learning of Mixed Tasks—0
A Framework for Few-Shot Policy Transfer through Observation Mapping and Behavior CloningCode0
BanglaNLP at BLP-2023 Task 2: Benchmarking different Transformer Models for Sentiment Analysis of Bangla Social Media PostsCode0
A Hybrid Transfer Learning Assisted Decision Support System for Accurate Prediction of Alzheimer Disease—0
Scalarization for Multi-Task and Multi-Domain Learning at Scale—0
Learning to Adapt SAM for Segmenting Cross-domain Point Clouds—0
HierarchicalContrast: A Coarse-to-Fine Contrastive Learning Framework for Cross-Domain Zero-Shot Slot FillingCode0
Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning—0
Defect Analysis of 3D Printed Cylinder Object Using Transfer Learning Approaches—0
CleftGAN: Adapting A Style-Based Generative Adversarial Network To Create Images Depicting Cleft Lip DeformityCode0
Self-supervised visual learning for analyzing firearms trafficking activities on the Web—0
Learning Transferable Conceptual Prototypes for Interpretable Unsupervised Domain Adaptation—0
A Recent Survey of Heterogeneous Transfer LearningCode1
Exploiting Semantic Localization in Highly Dynamic Wireless Networks Using Deep Homoscedastic Domain AdaptationCode0
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains—0
DeePref: Deep Reinforcement Learning For Video Prefetching In Content Delivery Networks—0
Domain-invariant Clinical Representation Learning by Bridging Data Distribution Shift across EMR Datasets—0
Give and Take: Federated Transfer Learning for Industrial IoT Network Intrusion Detection—0
GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning—0
Automatic Control of Reactive Brain Computer Interfaces—0
Efficient Adaptation of Large Vision Transformer via Adapter Re-ComposingCode1
Distributed Transfer Learning with 4th Gen Intel Xeon Processors—0
HoloFed: Environment-Adaptive Positioning via Multi-band Reconfigurable Holographic Surfaces and Federated Learning—0
Self-Supervised Dataset Distillation for Transfer LearningCode1
Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controlsCode0
Advancing Transformer's Capabilities in Commonsense ReasoningCode0
Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks—0
Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extraction—0
Cultural Compass: Predicting Transfer Learning Success in Offensive Language Detection with Cultural FeaturesCode0
EViT: An Eagle Vision Transformer with Bi-Fovea Self-AttentionCode1
Advancing Diagnostic Precision: Leveraging Machine Learning Techniques for Accurate Detection of Covid-19, Pneumonia, and Tuberculosis in Chest X-Ray Images—0
Understanding Transfer Learning and Gradient-Based Meta-Learning TechniquesCode0
Empirical Evaluation of the Segment Anything Model (SAM) for Brain Tumor Segmentation—0
Investigating Continuous Learning in Spiking Neural Networks—0
A Simple and Robust Framework for Cross-Modality Medical Image Segmentation applied to Vision TransformersCode1
Hierarchical Side-Tuning for Vision Transformers—0
Neutral TTS Female Voice Corpus in Brazilian Portuguese—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