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 51–100 of 10307 papers

TitleStatusHype
An Effective End-to-End Solution for Multimodal Action Recognition—0
Auto-Compressing Networks—0
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning ApproachCode0
An Explainable Deep Learning Framework for Brain Stroke and Tumor Progression via MRI Interpretation—0
Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment—0
Data-Efficient Challenges in Visual Inductive Priors: A Retrospective—0
Robust Evolutionary Multi-Objective Network Architecture Search for Reinforcement Learning (EMNAS-RL)—0
Do MIL Models Transfer?Code2
SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging SegmentationCode0
Variational Supervised Contrastive Learning—0
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine LearningCode0
CrosswalkNet: An Optimized Deep Learning Framework for Pedestrian Crosswalk Detection in Aerial Images with High-Performance Computing—0
ETT-CKGE: Efficient Task-driven Tokens for Continual Knowledge Graph EmbeddingCode0
Flowing Datasets with Wasserstein over Wasserstein Gradient FlowsCode1
Transfer Learning and Explainable AI for Brain Tumor Classification: A Study Using MRI Data from Bangladesh—0
Exploring Image Transforms derived from Eye Gaze Variables for Progressive Autism Diagnosis—0
The OCR Quest for Generalization: Learning to recognize low-resource alphabets with model editing—0
Textile Analysis for Recycling Automation using Transfer Learning and Zero-Shot Foundation Models—0
When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration—0
DiCoRe: Enhancing Zero-shot Event Detection via Divergent-Convergent LLM Reasoning—0
OpenAg: Democratizing Agricultural Intelligence—0
Generating Synthetic Stereo Datasets using 3D Gaussian Splatting and Expert Knowledge Transfer—0
LESS: Large Language Model Enhanced Semi-Supervised Learning for Speech Foundational Models—0
Self-Composing Policies for Scalable Continual Reinforcement Learning—0
Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning—0
Beamforming and Resource Allocation for Delay Optimization in RIS-Assisted OFDM Systems—0
TokAlign: Efficient Vocabulary Adaptation via Token AlignmentCode1
HtFLlib: A Comprehensive Heterogeneous Federated Learning Library and BenchmarkCode3
StARS DCM: A Sleep Stage-Decoding Forehead EEG Patch for Real-time Modulation of Sleep Physiology—0
Multi-Platform Methane Plume Detection via Model and Domain Adaptation—0
EfficientFER: EfficientNetv2 Based Deep Learning Approach for Facial Expression RecognitionCode1
TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species GenerationCode0
Getting More from Less: Transfer Learning Improves Sleep Stage Decoding Accuracy in Peripheral Wearable Devices—0
Neuro2Semantic: A Transfer Learning Framework for Semantic Reconstruction of Continuous Language from Human Intracranial EEGCode1
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning—0
Lightweight Convolutional Neural Networks for Retinal Disease Classification—0
Progressive Class-level Distillation—0
Unleashing the Power of Intermediate Domains for Mixed Domain Semi-Supervised Medical Image SegmentationCode0
Conformal Prediction for Zero-Shot ModelsCode1
LLMs Are Globally Multilingual Yet Locally Monolingual: Exploring Knowledge Transfer via Language and Thought Theory—0
Proactive Guidance of Multi-Turn Conversation in Industrial Search—0
Improving Language and Modality Transfer in Translation by Character-level Modeling—0
Attractor learning for spatiotemporally chaotic dynamical systems using echo state networks with transfer learning—0
Zero-Shot Adaptation of Parameter-Efficient Fine-Tuning in Diffusion Models—0
Personalized Subgraph Federated Learning with Differentiable Auxiliary Projections—0
BIRD: Behavior Induction via Representation-structure Distillation—0
To Trust Or Not To Trust Your Vision-Language Model's PredictionCode1
Epistemic Errors of Imperfect Multitask Learners When Distributions Shift—0
Graph Positional Autoencoders as Self-supervised Learners—0
FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series ClassificationCode1
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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