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 8151–8175 of 10307 papers

TitleStatusHype
New Insight in Cervical Cancer Diagnosis Using Convolution Neural Network Architecture—0
New Transfer Learning Techniques for Disparate Label Sets—0
New Vietnamese Corpus for Machine Reading Comprehension of Health News Articles—0
AgileGAN3D: Few-Shot 3D Portrait Stylization by Augmented Transfer Learning—0
NICT's Supervised Neural Machine Translation Systems for the WMT19 News Translation Task—0
NICT's Supervised Neural Machine Translation Systems for the WMT19 Translation Robustness Task—0
NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks—0
A Gift From Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning—0
NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to tackle Internet Humor—0
NITE: A Neural Inductive Teaching Framework for Domain Specific NER—0
NITK-IT_NLP@NSURL2019: Transfer Learning based POS Tagger for Under Resourced Bhojpuri and Magahi Language—0
NLM at MEDIQA 2021: Transfer Learning-based Approaches for Consumer Question and Multi-Answer Summarization—0
NLNDE at SemEval-2023 Task 12: Adaptive Pretraining and Source Language Selection for Low-Resource Multilingual Sentiment Analysis—0
Accelerating Dependency Graph Learning from Heterogeneous Categorical Event Streams via Knowledge Transfer—0
nlpBDpatriots at BLP-2023 Task 2: A Transfer Learning Approach to Bangla Sentiment Analysis—0
NLP-CIC-WFU at SocialDisNER: Disease Mention Extraction in Spanish Tweets Using Transfer Learning and Search by Propagation—0
NLP in the DH pipeline: Transfer-learning to a Chronolect—0
Aggression Identification in Social Media: a Transfer Learning Based Approach—0
NodeTrans: A Graph Transfer Learning Approach for Traffic Prediction—0
Nodule2vec: a 3D Deep Learning System for Pulmonary Nodule Retrieval Using Semantic Representation—0
NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation—0
Noise-Aware Training of Layout-Aware Language Models—0
Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning—0
Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware—0
The Empirical Impact of Forgetting and Transfer in Continual Visual Odometry—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