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 1351–1400 of 10307 papers

TitleStatusHype
A Competition Winning Deep Reinforcement Learning Agent in microRTSCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
Deep Transfer Learning Baselines for Sentiment Analysis in RussianCode1
AVocaDo: Strategy for Adapting Vocabulary to Downstream DomainCode1
DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing from Decentralised DataCode1
Deep Subdomain Adaptation Network for Image ClassificationCode1
Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and RetrievalCode1
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural NetworksCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
GraphAdapter: Tuning Vision-Language Models With Dual Knowledge GraphCode1
Bert4XMR: Cross-Market Recommendation with Bidirectional Encoder Representations from TransformerCode1
GoEmotions: A Dataset of Fine-Grained EmotionsCode1
Going deeper with Image TransformersCode1
Deep Transferring QuantizationCode1
One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and ClassificationCode1
DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation LearningCode1
DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String MatchingCode1
On Latency Predictors for Neural Architecture SearchCode1
DeiT III: Revenge of the ViTCode1
BadMerging: Backdoor Attacks Against Model MergingCode1
Denoised Self-Augmented Learning for Social RecommendationCode1
Bag of Tricks for Image Classification with Convolutional Neural NetworksCode1
Delving into Masked Autoencoders for Multi-Label Thorax Disease ClassificationCode1
Association Graph Learning for Multi-Task Classification with Category ShiftsCode1
Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine TranslationCode1
DenseShift: Towards Accurate and Efficient Low-Bit Power-of-Two QuantizationCode1
DEPARA: Deep Attribution Graph for Deep Knowledge TransferabilityCode1
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language UnderstandingCode1
GOAL: A Generalist Combinatorial Optimization Agent LearningCode1
Anatomical Foundation Models for Brain MRIsCode1
Synthetic optical coherence tomography angiographs for detailed retinal vessel segmentation without human annotationsCode1
Golos: Russian Dataset for Speech ResearchCode1
Graph Contrastive Learning with AugmentationsCode1
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge TransferCode1
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning ParadigmsCode1
A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive FusionCode1
BARThez: a Skilled Pretrained French Sequence-to-Sequence ModelCode1
Overcoming Data Limitations: A Few-Shot Specific Emitter Identification Method Using Self-Supervised Learning and Adversarial AugmentationCode1
A Survey on Negative TransferCode1
Detection and Classification of Diabetic Retinopathy using Deep Learning Algorithms for Segmentation to Facilitate Referral Recommendation for Test and Treatment PredictionCode1
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification TasksCode1
PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph CompletionCode1
Enhanced Gaussian Process Dynamical Models with Knowledge Transfer for Long-term Battery Degradation ForecastingCode1
Benchmarking Detection Transfer Learning with Vision TransformersCode1
Determining Chess Game State From an ImageCode1
Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural NetworksCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
Reasoning Visual Dialog with Sparse Graph Learning and Knowledge TransferCode1
Geometric Knowledge Distillation: Topology Compression for Graph Neural NetworksCode1
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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