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 8351–8400 of 10307 papers

TitleStatusHype
Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection—0
Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection—0
Differentially Private Prototypes for Imbalanced Transfer Learning—0
Beyond Transfer Learning: Co-finetuning for Action Localisation—0
Beyond Vanilla Fine-Tuning: Leveraging Multistage, Multilingual, and Domain-Specific Methods for Low-Resource Machine Translation—0
A Comprehensive Survey of Sentence Representations: From the BERT Epoch to the ChatGPT Era and Beyond—0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
BhamNLP at SemEval-2020 Task 12: An Ensemble of Different Word Embeddings and Emotion Transfer Learning for Arabic Offensive Language Identification in Social Media—0
Biasing & Debiasing based Approach Towards Fair Knowledge Transfer for Equitable Skin Analysis—0
Bias Mitigation in Fine-tuning Pre-trained Models for Enhanced Fairness and Efficiency—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
Bibliometric-enhanced Information Retrieval: 2nd International BIR Workshop—0
Bidirectional Brain Image Translation using Transfer Learning from Generic Pre-trained Models—0
Bidirectional Language Models Are Also Few-shot Learners—0
Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation—0
Bi-Directional Semi-Supervised Training of Convolutional Neural Networks for Ultrasound Elastography Displacement Estimation—0
BIGSAGE: unsupervised inductive representation learning of graph via bi-attended sampling and global-biased aggregating—0
Bi-level Unbalanced Optimal Transport for Partial Domain Adaptation—0
Bilinear classifiers for visual recognition—0
Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition—0
Bilingual Language Modeling, A transfer learning technique for Roman Urdu—0
Bilingual Transfer Learning for Online Product Classification—0
Binary Classification of Alzheimer Disease using sMRI Imaging modality and Deep Learning—0
Binary Paragraph Vectors—0
BiNet: Degraded-Manuscript Binarization in Diverse Document Textures and Layouts using Deep Encoder-Decoder Networks—0
BioAMA: Towards an End to End BioMedical Question Answering System—0
BioBERTpt - A Portuguese Neural Language Model for Clinical Named Entity Recognition—0
BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network—0
Biologically inspired sleep algorithm for artificial neural networks—0
Biological neurons act as generalization filters in reservoir computing—0
Bio-Measurements Estimation and Support in Knee Recovery through Machine Learning—0
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation—0
BioNCERE: Non-Contrastive Enhancement For Relation Extraction In Biomedical Texts—0
BIOWISH: Biometric Recognition using Wearable Inertial Sensors detecting Heart Activity—0
BIRD: Behavior Induction via Representation-structure Distillation—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
Blessing of Class Diversity in Pre-training—0
Blockchain as an Enabler for Transfer Learning in Smart Environments—0
Block Toeplitz Sparse Precision Matrix Estimation for Large-Scale Interval-Valued Time Series Forecasting—0
BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning—0
BNS: Building Network Structures Dynamically for Continual Learning—0
Bombus Species Image Classification—0
Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2—0
Boosted Zero-Shot Learning with Semantic Correlation Regularization—0
Boosting Automatic COVID-19 Detection Performance with Self-Supervised Learning and Batch Knowledge Ensembling—0
Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation—0
Boosting Deep Face Recognition via Disentangling Appearance and Geometry—0
Boosting Deep Transfer Learning for COVID-19 Classification—0
Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and Local Consensus Guided Cross Attention—0
Boosting HDR Image Reconstruction via Semantic Knowledge Transfer—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