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 2151–2200 of 10307 papers

TitleStatusHype
A synthetic data approach for domain generalization of NLI models—0
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network GenerationCode2
Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks—0
LEIA: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data AugmentationCode1
Mitigating Catastrophic Forgetting in Multi-domain Chinese Spelling Correction by Multi-stage Knowledge Transfer Framework—0
Autocorrect for Estonian texts: final report from project EKTB25—0
A Question Answering Based Pipeline for Comprehensive Chinese EHR Information Extraction—0
ZeroG: Investigating Cross-dataset Zero-shot Transferability in GraphsCode1
An end-to-end attention-based approach for learning on graphsCode2
Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary InformationCode0
Robust agents learn causal world models—0
Differential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection—0
Multiview Contrastive Learning for Unsupervised Domain Adaptation in Brain–Computer Interfaces—0
BrainWave: A Brain Signal Foundation Model for Clinical ApplicationsCode1
Data Augmentation and Transfer Learning Approaches Applied to Facial Expressions Recognition—0
Towards Precision Cardiovascular Analysis in Zebrafish: The ZACAF Paradigm—0
Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks—0
How does Your RL Agent Explore? An Optimal Transport Analysis of Occupancy Measure Trajectories—0
Evaluation of Activated Sludge Settling Characteristics from Microscopy Images with Deep Convolutional Neural Networks and Transfer LearningCode0
Few-Shot Object Detection with Sparse Context Transformers—0
Subgraph Pooling: Tackling Negative Transfer on GraphsCode0
Bayesian Multi-Task Transfer Learning for Soft Prompt TuningCode0
Enabling Multi-Agent Transfer Reinforcement Learning via Scenario Independent Representation—0
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter SharingCode1
Convolutional Neural Networks Towards Facial Skin Lesions Detection—0
A Competition Winning Deep Reinforcement Learning Agent in microRTSCode1
Text Detoxification as Style Transfer in English and HindiCode0
Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging ClassificationCode0
MODIPHY: Multimodal Obscured Detection for IoT using PHantom Convolution-Enabled Faster YOLOCode1
Multi-Modal Emotion Recognition by Text, Speech and Video Using Pretrained Transformers—0
An Optimization Framework for Processing and Transfer Learning for the Brain Tumor SegmentationCode0
Should I try multiple optimizers when fine-tuning pre-trained Transformers for NLP tasks? Should I tune their hyperparameters?—0
Transfer learning with generative models for object detection on limited datasets—0
Embedding Compression for Teacher-to-Student Knowledge Transfer—0
Transferring facade labels between point clouds with semantic octrees while considering change detectionCode0
BarlowTwins-CXR : Enhancing Chest X-Ray abnormality localization in heterogeneous data with cross-domain self-supervised learning—0
Attention-Enhanced Prioritized Proximal Policy Optimization for Adaptive Edge Caching—0
Text-to-Code Generation with Modality-relative Pre-training—0
PLAPT: Protein-Ligand Binding Affinity Prediction Using Pretrained TransformersCode2
Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning—0
Group Distributionally Robust Dataset Distillation with Risk MinimizationCode1
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph TransformersCode2
Scaling Laws for Downstream Task Performance of Large Language Models—0
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation ModelsCode1
Symbol Correctness in Deep Neural Networks Containing Symbolic Layers—0
Enhancing textual textbook question answering with large language models and retrieval augmented generationCode0
Constrained Decoding for Cross-lingual Label ProjectionCode0
Survival and grade of the glioma prediction using transfer learning—0
Pruner: A Speculative Exploration Mechanism to Accelerate Tensor Program TuningCode1
Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot 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