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 451–500 of 10307 papers

TitleStatusHype
AugFL: Augmenting Federated Learning with Pretrained ModelsCode0
Generalized Diffusion Detector: Mining Robust Features from Diffusion Models for Domain-Generalized DetectionCode1
Conditional Electrocardiogram Generation Using Hierarchical Variational Autoencoders—0
Diagnosis of Patients with Viral, Bacterial, and Non-Pneumonia Based on Chest X-Ray Images Using Convolutional Neural Networks—0
Hyperspectral Image Restoration and Super-resolution with Physics-Aware Deep Learning for Biomedical Applications—0
A General Neural Network Potential for Energetic Materials with C, H, N, and O elementsCode1
A Zero-Shot Learning Approach for Ephemeral Gully Detection from Remote Sensing using Vision Language Models—0
An Efficient Approach to Detecting Lung Nodules Using Swin Transformer—0
A Transfer Framework for Enhancing Temporal Graph Learning in Data-Scarce Settings—0
Asynchronous Personalized Federated Learning through Global Memorization—0
Rapid morphology characterization of two-dimensional TMDs and lateral heterostructures based on deep learningCode0
Towards Understanding the Benefit of Multitask Representation Learning in Decision Process—0
Fine-tuning machine-learned particle-flow reconstruction for new detector geometries in future colliders—0
MIGE: A Unified Framework for Multimodal Instruction-Based Image Generation and EditingCode2
ECLeKTic: a Novel Challenge Set for Evaluation of Cross-Lingual Knowledge Transfer—0
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion—0
Foundation-Model-Boosted Multimodal Learning for fMRI-based Neuropathic Pain Drug Response PredictionCode0
RuCCoD: Towards Automated ICD Coding in RussianCode0
Long-Context Inference with Retrieval-Augmented Speculative DecodingCode1
Transfer Learning in Latent Contextual Bandits with Covariate Shift Through Causal TransportabilityCode0
Exploring Open-world Continual Learning with Knowns-Unknowns Knowledge TransferCode0
Deep Convolutional Neural Networks for Palm Fruit Maturity ClassificationCode0
Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage PerspectiveCode0
GraphBridge: Towards Arbitrary Transfer Learning in GNNsCode0
Deep Learning-Based Transfer Learning for Classification of Cassava Disease—0
A Sample-Level Evaluation and Generative Framework for Model Inversion AttacksCode0
Transfer Learning Assisted Fast Design Migration Over Technology Nodes: A Study on Transformer Matching NetworkCode1
Transfer Learning for Transient Classification: From Simulations to Real Data and ZTF to LSST—0
Conformal Prediction Under Generalized Covariate Shift with Posterior Drift—0
Language Models' Factuality Depends on the Language of InquiryCode0
Geometric Properties and Graph-Based Optimization of Neural Networks: Addressing Non-Linearity, Dimensionality, and Scalability—0
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models—0
Rewards-based image analysis in microscopy—0
Multimodal Bearing Fault Classification Under Variable Conditions: A 1D CNN with Transfer Learning—0
Diagnosing COVID-19 Severity from Chest X-Ray Images Using ViT and CNN ArchitecturesCode0
AUKT: Adaptive Uncertainty-Guided Knowledge Transfer with Conformal Prediction—0
Recurrent Knowledge Identification and Fusion for Language Model Continual Learning—0
Iterative Auto-Annotation for Scientific Named Entity Recognition Using BERT-Based Models—0
Joint Similarity Item Exploration and Overlapped User Guidance for Multi-Modal Cross-Domain Recommendation—0
Separated Contrastive Learning for Matching in Cross-domain Recommendation with Curriculum Scheduling—0
TabMixer: advancing tabular data analysis with an enhanced MLP-mixer approachCode1
CSTRL: Context-Driven Sequential Transfer Learning for Abstractive Radiology Report SummarizationCode0
TransMamba: Fast Universal Architecture Adaption from Transformers to Mamba—0
Graph Attention Convolutional U-NET: A Semantic Segmentation Model for Identifying Flooded Areas—0
Multimodal Quantitative Language for Generative Recommendation—0
Evolutionary Algorithms Approach For Search Based On Semantic Document Similarity—0
FedMobile: Enabling Knowledge Contribution-aware Multi-modal Federated Learning with Incomplete Modalities—0
Multi-dataset synergistic in supervised learning to pre-label structural components in point clouds from shell construction scenes—0
Edit Once, Update Everywhere: A Simple Framework for Cross-Lingual Knowledge Synchronization in LLMs—0
Asymmetric Co-Training for Source-Free Few-Shot Domain AdaptationCode0
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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