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 44014450 of 6439 papers

TitleStatusHype
A simple baseline for domain adaptation using rotation prediction0
A Simple but Effective Pluggable Entity Lookup Table for Pre-trained Language Models0
A simple method for domain adaptation of sentence embeddings0
A Simple Unified Information Regularization Framework for Multi-Source Domain Adaptation0
A Simplification-Translation-Restoration Framework for Cross-Domain SMT Applications0
ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling0
ASR Error Correction and Domain Adaptation Using Machine Translation0
ASR Error Correction using Large Language Models0
Assessing the State of Self-Supervised Human Activity Recognition using Wearables0
Assessing the Value of Transfer Learning Metrics for RF Domain Adaptation0
Assessment of Transformer-Based Encoder-Decoder Model for Human-Like Summarization0
Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection0
Associative Partial Domain Adaptation0
A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging0
A Student-Teacher Architecture for Dialog Domain Adaptation under the Meta-Learning Setting0
A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition0
A Study of Style in Machine Translation: Controlling the Formality of Machine Translation Output0
A Study of Unsupervised Evaluation Metrics for Practical and Automatic Domain Adaptation0
A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 20230
A Study on Unsupervised Domain Adaptation for Semantic Segmentation in the Era of Vision-Language Models0
A Sui Generis QA Approach using RoBERTa for Adverse Drug Event Identification0
A Survey of Circuit Foundation Model: Foundation AI Models for VLSI Circuit Design and EDA0
A Survey of Domain Adaptation for Neural Machine Translation0
A Survey of IMU Based Cross-Modal Transfer Learning in Human Activity Recognition0
A Survey of Unsupervised Domain Adaptation for Visual Recognition0
A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets0
A Survey on Deep Domain Adaptation for LiDAR Perception0
A Survey on Deep Hashing Methods0
A survey on domain adaptation theory: learning bounds and theoretical guarantees0
A Survey on Optimal Transport for Machine Learning: Theory and Applications0
A Survey on Vietnamese Document Analysis and Recognition: Challenges and Future Directions0
Asymmetrical Latent Representation for Individual Treatment Effect Modeling0
Asymmetric Mutual Learning for Multi-source Unsupervised Sentiment Adaptation with Dynamic Feature Network0
Critically examining the Domain Generalizability of Facial Expression Recognition models0
A Systematic Evaluation of Domain Adaptation Algorithms On Time Series Data0
A Theory of Label Propagation for Subpopulation Shift0
A Theory of Learning Unified Model via Knowledge Integration from Label Space Varying Domains0
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data0
A Theory of Output-Side Unsupervised Domain Adaptation0
ATPL: Mutually enhanced adversarial training and pseudo labeling for unsupervised domain adaptation0
Attentional Road Safety Networks0
Attention-Aware Age-Agnostic Visual Place Recognition0
Attention-based Cross-Layer Domain Alignment for Unsupervised Domain Adaptation0
Attention-based Domain Adaptation for Single Stage Detectors0
Attention-based Domain Adaption Using Transfer Learning for Part-of-Speech Tagging: An Experiment on the Hindi language0
Attention Bridging Network for Knowledge Transfer0
Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI0
Attention Regularized Laplace Graph for Domain Adaptation0
Attentive Continuous Generative Self-training for Unsupervised Domain Adaptive Medical Image Translation0
Attentive Temporal Pooling for Conformer-based Streaming Language Identification in Long-form Speech0
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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