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 701–750 of 10307 papers

TitleStatusHype
Federated Continual Learning with Weighted Inter-client TransferCode1
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP TasksCode1
Bridge Correlational Neural Networks for Multilingual Multimodal Representation LearningCode1
Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple ClassifierCode1
Few-Shot Keyword Spotting in Any LanguageCode1
Deep Recurrent Neural Networks for ECG Signal DenoisingCode1
Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot FillingCode1
Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language ModelsCode1
Bridging Anaphora Resolution as Question AnsweringCode1
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate DomainsCode1
A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species ClassificationCode1
Broken Neural Scaling LawsCode1
Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved TransferabilityCode1
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load ForecastingCode1
DeepShadows: Separating Low Surface Brightness Galaxies from Artifacts using Deep LearningCode1
Fine-tuning giant neural networks on commodity hardware with automatic pipeline model parallelismCode1
Calibration-free online test-time adaptation for electroencephalography motor imagery decodingCode1
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modelingCode1
Can LLMs' Tuning Methods Work in Medical Multimodal Domain?Code1
An Empirical Analysis of Image-Based Learning Techniques for Malware ClassificationCode1
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?Code1
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image ClassificationCode1
ArtNeRF: A Stylized Neural Field for 3D-Aware Cartoonized Face SynthesisCode1
ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from TransformerCode1
Flight Contrail Segmentation via Augmented Transfer Learning with Novel SR Loss Function in Hough SpaceCode1
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World DomainsCode1
FNet: Mixing Tokens with Fourier TransformsCode1
Deeply Coupled Cross-Modal Prompt LearningCode1
An Empirical Study on Cross-X Transfer for Legal Judgment PredictionCode1
An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot LabelsCode1
A simple, efficient and scalable contrastive masked autoencoder for learning visual representationsCode1
Deep Metric Learning for Unsupervised Remote Sensing Change DetectionCode1
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer LearningCode1
Frequency Attention for Knowledge DistillationCode1
DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing from Decentralised DataCode1
An Encoder-Decoder Based Audio Captioning System With Transfer and Reinforcement LearningCode1
A Deep Learning-Based Supervised Transfer Learning Framework for DOA Estimation with Array ImperfectionsCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural RepresentationsCode1
Fruit Quality and Defect Image Classification with Conditional GAN Data AugmentationCode1
Chaos as an interpretable benchmark for forecasting and data-driven modellingCode1
Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric ModelsCode1
A deep learning framework for solution and discovery in solid mechanicsCode1
CheXWorld: Exploring Image World Modeling for Radiograph Representation LearningCode1
Choquet Integral and Coalition Game-based Ensemble of Deep Learning Models for COVID-19 Screening from Chest X-ray ImagesCode1
GEAL: Generalizable 3D Affordance Learning with Cross-Modal ConsistencyCode1
A Comprehensive Survey on Transfer LearningCode1
ChrEn: Cherokee-English Machine Translation for Endangered Language RevitalizationCode1
CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel SynthesisCode1
DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation LearningCode1
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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