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 5151–5200 of 10307 papers

TitleStatusHype
Unbiased Scene Graph Generation using Predicate Similarities—0
Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond—0
The (In)Effectiveness of Intermediate Task Training For Domain Adaptation and Cross-Lingual Transfer Learning—0
On The Effects Of Data Normalisation For Domain Adaptation On EEG Data—0
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization—0
Automated Identification of Tree Species by Bark Texture Classification Using Convolutional Neural Networks—0
An Analysis of RF Transfer Learning Behavior Using Synthetic Data—0
PCONet: A Convolutional Neural Network Architecture to Detect Polycystic Ovary Syndrome (PCOS) from Ovarian Ultrasound Images—0
DARE: A large-scale handwritten date recognition system—0
Taking Actions Separately: A Bidirectionally-Adaptive Transfer Learning Method for Low-Resource Neural Machine Translation—0
Can Attention-based Transformers Explain or Interpret Cyberbullying Detection?—0
Argument Novelty and Validity Assessment via Multitask and Transfer Learning—0
Knowledge Distillation with Reptile Meta-Learning for Pretrained Language Model CompressionCode0
MECI: A Multilingual Dataset for Event Causality IdentificationCode0
Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering—0
How to Parse a Creole: When Martinican Creole Meets French—0
Can We Guide a Multi-Hop Reasoning Language Model to Incrementally Learn at Each Single-Hop?Code0
Knowledge Transfer with Visual Prompt in multi-modal Dialogue Understanding and Generation—0
基于知识迁移的情感-原因对抽取(Emotion-Cause Pair Extraction Based on Knowledge-Transfer)—0
Analyzing BERT Cross-lingual Transfer Capabilities in Continual Sequence LabelingCode0
Cluster-aware Pseudo-Labeling for Supervised Open Relation ExtractionCode0
Language Branch Gated Multilingual Neural Machine Translation—0
Machine Translation for a Very Low-Resource Language - Layer Freezing Approach on Transfer Learning—0
Detection of Negative Campaign in Israeli Municipal ElectionsCode0
Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun EntailmentCode0
Supervised Contrastive Learning for Cross-lingual Transfer Learning—0
Multi-Stage Framework with Refinement Based Point Set Registration for Unsupervised Bi-Lingual Word Alignment—0
Document-level Event Factuality Identification via Machine Reading Comprehension Frameworks with Transfer Learning—0
Continual Few-shot Intent Detection—0
Multiple Pivot Languages and Strategic Decoder Initialization Helps Neural Machine Translation—0
Exploring Multimodal Features and Fusion Strategies for Analyzing Disaster Tweets—0
Continually Detection, Rapidly React: Unseen Rumors Detection Based on Continual Prompt-Tuning—0
NLP-CIC-WFU at SocialDisNER: Disease Mention Extraction in Spanish Tweets Using Transfer Learning and Search by Propagation—0
Transfer Learning for Individual Treatment Effect Estimation—0
Improving Commonsense Contingent Reasoning by Pseudo-data and Its Application to the Related Tasks—0
Transfer Learning Improves French Cross-Domain Dialect Identification: NRC @ VarDial 2022—0
Unregulated Chinese-to-English Data Expansion Does NOT Work for Neural Event Detection—0
Virtual Knowledge Graph Construction for Zero-Shot Domain-Specific Document RetrievalCode0
Transferring Confluent Knowledge to Argument MiningCode0
Towards a Unified View of Affinity-Based Knowledge Distillation—0
Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models—0
Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods—0
Evaluation of taxonomic and neural embedding methods for calculating semantic similarity—0
Leveraging Industry 4.0 -- Deep Learning, Surrogate Model and Transfer Learning with Uncertainty Quantification Incorporated into Digital Twin for Nuclear System—0
Bidirectional Language Models Are Also Few-shot Learners—0
How to tackle an emerging topic? Combining strong and weak labels for Covid news NERCode0
Facial Landmark Predictions with Applications to MetaverseCode0
Cyclegan Network for Sheet Metal Welding Drawing Translation—0
Learning Deep Representations via Contrastive Learning for Instance Retrieval—0
Data Augmentation using Feature Generation for Volumetric Medical Images—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