SOTAVerified

Domain Adaptation

Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Further readings:

( Image credit: Unsupervised Image-to-Image Translation Networks )

Papers

Showing 60516100 of 6439 papers

TitleStatusHype
Interpretable Dysarthric Speaker Adaptation based on Optimal-Transport0
Interpreting Stellar Spectra with Unsupervised Domain Adaptation0
Interventional Domain Adaptation0
In the Era of Prompt Learning with Vision-Language Models0
Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks0
InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization0
Invariant Representations for Noisy Speech Recognition0
Inverse Surrogate Model of a Soft X-Ray Spectrometer using Domain Adaptation0
Invertible Autoencoder for domain adaptation0
Investigating a domain adaptation approach for integrating different measurement instruments in a longitudinal clinical registry0
Investigating Catastrophic Forgetting During Continual Training for Neural Machine Translation0
Investigation on domain adaptation of additive manufacturing monitoring systems to enhance digital twin reusability0
Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysis0
Is Domain Adaptation Worth Your Investment? Comparing BERT and FinBERT on Financial Tasks0
Is Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks?0
ISTRBoost: Importance Sampling Transfer Regression using Boosting0
Iterative Alignment Flows0
Iterative Domain-Repaired Back-Translation0
Iterative Dual Domain Adaptation for Neural Machine Translation0
IT-RUDA: Information Theory Assisted Robust Unsupervised Domain Adaptation0
IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation0
Ixamed’s submission description for WMT20 Biomedical shared task: benefits and limitations of using terminologies for domain adaptation0
Jacobian Norm for Unsupervised Source-Free Domain Adaptation0
JaFIn: Japanese Financial Instruction Dataset0
Jane 2: Open Source Phrase-based and Hierarchical Statistical Machine Translation0
Japanese all-words WSD system using the Kyoto Text Analysis ToolKit0
JEAM: A Novel Model for Cross-Domain Sentiment Classification Based on Emotion Analysis0
Jitter Does Matter: Adapting Gaze Estimation to New Domains0
JoBimText Visualizer: A Graph-based Approach to Contextualizing Distributional Similarity0
Joint Attention-Driven Domain Fusion and Noise-Tolerant Learning for Multi-Source Domain Adaptation0
Joint autoencoders: a flexible meta-learning framework0
Joint auto-encoders: a flexible multi-task learning framework0
Joint cross-domain classification and subspace learning for unsupervised adaptation0
Joint domain adaptation and speech bandwidth extension using time-domain GANs for speaker verification0
Joint Emotion Analysis via Multi-task Gaussian Processes0
Joint Geometrical and Statistical Alignment for Visual Domain Adaptation0
Joint Information Preservation for Heterogeneous Domain Adaptation0
Joint Learning of Generative Translator and Classifier for Visually Similar Classes0
Joint Learning of Local and Global Features for Entity Linking via Neural Networks0
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition0
Joint Learning of Pre-Trained and Random Units for Domain Adaptation in Part-of-Speech Tagging0
Joint Multi-Domain Learning for Automatic Short Answer Grading0
Joint Partial Optimal Transport for Open Set Domain Adaptation0
Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation0
Joint Semantic Transfer Network for IoT Intrusion Detection0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation0
Joint semi-supervised and contrastive learning enables domain generalization and multi-domain segmentation0
Joint Similarity Item Exploration and Overlapped User Guidance for Multi-Modal Cross-Domain Recommendation0
Joint Source-Environment Adaptation for Deep Learning-Based Underwater Acoustic Source Ranging0
Joint Training for Neural Machine Translation Models with Monolingual Data0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FFTATAverage Accuracy96Unverified
2PMTransAverage Accuracy95.3Unverified
3CMKDAverage Accuracy94.4Unverified
4SSRT-B (ours)Average Accuracy93.5Unverified
5CDTransAverage Accuracy92.6Unverified
6CoViAverage Accuracy91.8Unverified
7GSDEAverage Accuracy91.7Unverified
8FixBiAverage Accuracy91.4Unverified
9Contrastive Adaptation NetworkAverage Accuracy90.6Unverified
10BIWAAAverage Accuracy90.5Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU78.1Unverified
2ILM-ASSLmIoU76.6Unverified
3DCFmIoU69.3Unverified
4HRDA+PiPamIoU68.2Unverified
5MICmIoU67.3Unverified
6FREDOM - TransformermIoU67Unverified
7HRDAmIoU65.8Unverified
8SePiComIoU64.3Unverified
9MIC + Guidance TrainingmIoU63.8Unverified
10DAFormer + ProCSTmIoU61.6Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU77.8Unverified
2DCFmIoU77.7Unverified
3ILM-ASSLmIoU76.1Unverified
4MICmIoU75.9Unverified
5HRDA+PiPamIoU75.6Unverified
6HRDAmIoU73.8Unverified
7FREDOM - TransformermIoU73.6Unverified
8HALOmIoU73.3Unverified
9SePiComIoU70.3Unverified
10DAFormer + ProCSTmIoU69.4Unverified
#ModelMetricClaimedVerifiedStatus
1SWGAccuracy92.3Unverified
2RCLAccuracy90Unverified
3PGA (ViT-L/14)Accuracy89.4Unverified
4PMTransAccuracy89Unverified
5CMKDAccuracy89Unverified
6MICAccuracy86.2Unverified
7PGA (ViT-B/16)Accuracy85.1Unverified
8ELSAccuracy84.6Unverified
9SDAT (ViT-B/16)Accuracy84.3Unverified
10CDTrans (DeiT-B)Accuracy80.5Unverified
#ModelMetricClaimedVerifiedStatus
1FFTATAccuracy93.8Unverified
2RCLAccuracy93.2Unverified
3MICAccuracy92.8Unverified
4SWGAccuracy92.7Unverified
5CMKDAccuracy91.8Unverified
6DePTAccuracy90.7Unverified
7SDAT(ViT)Accuracy89.8Unverified
8SFDA2++Accuracy89.6Unverified
9PMtransAccuracy88.8Unverified
10CoViAccuracy88.5Unverified
#ModelMetricClaimedVerifiedStatus
1CMKDAccuracy94.3Unverified
2MCC+NWDAccuracy90.7Unverified
3GLOT-DRAccuracy90.4Unverified
4SPLAccuracy90.3Unverified
5DFA-SAFNAccuracy90.2Unverified
6DADAAccuracy89.3Unverified
7DFA-ENTAccuracy89.1Unverified
8MEDMAccuracy88.9Unverified
9DDAAccuracy88.9Unverified
10IAFN+ENTAccuracy88.9Unverified
#ModelMetricClaimedVerifiedStatus
1SoRAmIoU78.8Unverified
2ReinmIoU77.6Unverified
3CoDAmIoU72.6Unverified
4Refign (HRDA)mIoU72.1Unverified
5HALOmIoU71.9Unverified
6MICmIoU70.4Unverified
7HRDAmIoU68Unverified
8Refign (DAFormer)mIoU65.5Unverified
9VBLC (DAFormer)mIoU64.2Unverified
10CMFormermIoU60.1Unverified
#ModelMetricClaimedVerifiedStatus
1FACTAccuracy98.8Unverified
2FAMCDAccuracy98.72Unverified
3DFA-MCDAccuracy98.6Unverified
4Mean teacherAccuracy98.26Unverified
5DRANetAccuracy98.2Unverified
6SHOTAccuracy98Unverified
7DFA-ENTAccuracy97.9Unverified
8CyCleGAN (Light-weight Calibrator)Accuracy97.1Unverified