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 5501–5550 of 10307 papers

TitleStatusHype
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities—0
Parameter-Efficient Abstractive Question Answering over Tables and over Text—0
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents—0
Cross-domain Named Entity Recognition via Graph Matching—0
Meta-Adapter: Parameter Efficient Few-Shot Learning through Meta-Learning—0
Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models—0
Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages—0
Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-Modal Knowledge Transfer—0
All Birds with One Stone: Multi-task Learning for Inference with One Forward Pass—0
Persian Natural Language Inference: A Meta-learning approach—0
Synonyms, Antonyms and Beyond—0
Weight Squeezing: Reparameterization for Knowledge Transfer and Model Compression—0
XLTime: A Cross-Lingual Knowledge Transfer Framework for Zero-Shot Low-Resource Language Temporal Expression Extraction—0
Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment—0
Speech Synthesis for Low Resource Languages using Transliteration Enabled Transfer Learning—0
Gradient Sparsification For Masked Fine-Tuning of Transformers—0
Shallow Parsing for Nepal Bhasa Complement Clauses—0
Hierarchical transfer learning with applications for electricity load forecastingCode0
A Comparative Study on Transfer Learning and Distance Metrics in Semantic Clustering over the COVID-19 Tweets—0
Grounding Psychological Shape Space in Convolutional Neural NetworksCode1
Is One Teacher Model Enough to Transfer Knowledge to a Student Model?Code0
Joint Unsupervised and Supervised Training for Multilingual ASR—0
Say What? Collaborative Pop Lyric Generation Using Multitask Transfer Learning—0
Adding more data does not always help: A study in medical conversation summarization with PEGASUS—0
Continual Learning via Local Module CompositionCode1
Transfer Learning Capabilities of Untrained Neural Networks for MIMO CSI Recreation—0
Fracture Detection in Wrist X-ray Images Using Deep Learning-Based Object Detection ModelsCode0
Improving Compound Activity Classification via Deep Transfer and Representation LearningCode0
On Transferability of Prompt Tuning for Natural Language ProcessingCode1
Scalable Diverse Model Selection for Accessible Transfer LearningCode1
Automated PII Extraction from Social Media for Raising Privacy Awareness: A Deep Transfer Learning Approach—0
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection—0
CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks—0
Entropy optimized semi-supervised decomposed vector-quantized variational autoencoder model based on transfer learning for multiclass text classification and generation—0
A Two-Stage Approach towards Generalization in Knowledge Base Question Answering—0
Prune Once for All: Sparse Pre-Trained Language Models—0
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps—0
Learning to Generalize Compositionally by Transferring Across Semantic Parsing TasksCode0
TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary DataCode1
Enhancing Prototypical Few-Shot Learning by Leveraging the Local-Level Strategy—0
Reinforcement Learning for Mixed Autonomy IntersectionsCode1
Deep Neural Networks to Detect Weeds from Crops in Agricultural Environments in Real-Time: A ReviewCode2
Improved Regularization and Robustness for Fine-tuning in Neural NetworksCode1
Speaker Generation—0
Open-Set Crowdsourcing using Multiple-Source Transfer Learning—0
Action Recognition using Transfer Learning and Majority Voting for CSGO—0
Convolutional Gated MLP: Combining Convolutions & gMLP—0
Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language ModelingCode1
Sexism Identification in Tweets and Gabs using Deep Neural Networks—0
Data Selection for Efficient Model Update in Federated Learning—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