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 251–300 of 10307 papers

TitleStatusHype
Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning—0
π_0.5: a Vision-Language-Action Model with Open-World Generalization—0
SPECI: Skill Prompts based Hierarchical Continual Imitation Learning for Robot Manipulation—0
Transfer Learning for High-dimensional Reduced Rank Time Series Models—0
Research on Cloud Platform Network Traffic Monitoring and Anomaly Detection System based on Large Language Models—0
Fourier analysis of the physics of transfer learning for data-driven subgrid-scale models of ocean turbulence—0
Is Intelligence the Right Direction in New OS Scheduling for Multiple Resources in Cloud Environments?—0
Histogram-based Parameter-efficient Tuning for Passive Sonar ClassificationCode0
PIV-FlowDiffuser:Transfer-learning-based denoising diffusion models for PIVCode0
Turbo2K: Towards Ultra-Efficient and High-Quality 2K Video Synthesis—0
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive SurveyCode2
Empirical Evaluation of Knowledge Distillation from Transformers to Subquadratic Language Models—0
Enhancing Pothole Detection and Characterization: Integrated Segmentation and Depth Estimation in Road Anomaly Systems—0
A Deep Learning-Based Supervised Transfer Learning Framework for DOA Estimation with Array ImperfectionsCode1
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models—0
From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs—0
CheXWorld: Exploring Image World Modeling for Radiograph Representation LearningCode1
MetaDSE: A Few-shot Meta-learning Framework for Cross-workload CPU Design Space Exploration—0
Scaling Laws for Data-Efficient Visual Transfer Learning—0
Non-Uniform Class-Wise Coreset Selection: Characterizing Category Difficulty for Data-Efficient Transfer Learning—0
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification—0
Pandora: A Code-Driven Large Language Model Agent for Unified Reasoning Across Diverse Structured Knowledge—0
Transfer Learning via Auxiliary Labels with Application to Cold-Hardiness Prediction—0
Enhancing Cocoa Pod Disease Classification via Transfer Learning and Ensemble Methods: Toward Robust Predictive Modeling—0
Quantum Computing Supported Adversarial Attack-Resilient Autonomous Vehicle Perception Module for Traffic Sign ClassificationCode0
3D-PointZshotS: Geometry-Aware 3D Point Cloud Zero-Shot Semantic Segmentation Narrowing the Visual-Semantic GapCode0
Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets—0
Towards a Universal Vibration Analysis Dataset: A Framework for Transfer Learning in Predictive Maintenance and Structural Health Monitoring—0
TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics DataCode2
Meta-learning For Few-Shot Time Series Crop Type Classification: A Benchmark On The EuroCropsML DatasetCode0
Transfer Learning for Temporal Link PredictionCode0
Enhancing LLM-based Recommendation through Semantic-Aligned Collaborative Knowledge—0
UP-Person: Unified Parameter-Efficient Transfer Learning for Text-based Person RetrievalCode0
The Impact of Model Zoo Size and Composition on Weight Space LearningCode0
Progressive Transfer Learning for Multi-Pass Fundus Image Restoration—0
Learning to Harmonize Cross-vendor X-ray Images by Non-linear Image Dynamics Correction—0
Inferring genotype-phenotype maps using attention modelsCode0
Self-Controlled Dynamic Expansion Model for Continual Learning—0
Breaking the Data Barrier -- Building GUI Agents Through Task GeneralizationCode1
Transfer Learning Assisted XgBoost For Adaptable Cyberattack Detection In Battery Packs—0
MultiLoKo: a multilingual local knowledge benchmark for LLMs spanning 31 languagesCode1
Query-based Knowledge Transfer for Heterogeneous Learning Environments—0
Towards On-Device Learning and Reconfigurable Hardware Implementation for Encoded Single-Photon Signal Processing—0
Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes—0
Near-Driven Autonomous Rover Navigation in Complex Environments: Extensions to Urban Search-and-Rescue and Industrial Inspection—0
Boosting multi-demographic federated learning for chest x-ray analysis using general-purpose self-supervised representations—0
Banana Ripeness Level Classification using a Simple CNN Model Trained with Real and Synthetic Datasets—0
Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes—0
Conditional Data Synthesis Augmentation—0
Detect Anything 3D in the WildCode3
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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