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.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 4801–4825 of 6439 papers

Title	Date	Tasks	Status
Controlling Target Features in Neural Machine Translation via Prefix Constraints	Nov 1, 2017	Domain AdaptationMachine Translation	—Unverified
ControlUDA: Controllable Diffusion-assisted Unsupervised Domain Adaptation for Cross-Weather Semantic Segmentation	Feb 9, 2024	Domain AdaptationSemantic Segmentation	—Unverified
Conversational QA Dataset Generation with Answer Revision	Sep 23, 2022	Answer GenerationConversational Question Answering	—Unverified
Coping with low data availability for social media crisis message categorisation	May 26, 2023	Domain AdaptationMulti-Task Learning	—Unverified
Copy-Move Forgery Classification via Unsupervised Domain Adaptation	Nov 14, 2019	ClassificationDomain Adaptation	—Unverified
Co-regularization Based Semi-supervised Domain Adaptation	Dec 1, 2010	Domain AdaptationGeneralization Bounds	—Unverified
Co-regularized Alignment for Unsupervised Domain Adaptation	Nov 13, 2018	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Core Knowledge Learning Framework for Graph Adaptation and Scalability Learning	Jul 2, 2024	ClassificationDomain Adaptation	—Unverified
Corporate Bankruptcy Prediction with BERT Model	Nov 1, 2021	Domain AdaptationLanguage Modeling	—Unverified
Corporate Bankruptcy Prediction with Domain-Adapted BERT	Dec 6, 2023	Domain AdaptationLanguage Modeling	—Unverified
Corpus Annotation through Crowdsourcing: Towards Best Practice Guidelines	May 1, 2014	Domain AdaptationNatural Language Inference	—Unverified
Corpus-based Interpretation of Instructions in Virtual Environments	Jul 1, 2012	Domain AdaptationText Generation	—Unverified
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models	Sep 18, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Correction Focused Language Model Training for Speech Recognition	Oct 17, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Correlated Adversarial Joint Discrepancy Adaptation Network	May 18, 2021	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Correlation-aware Adversarial Domain Adaptation and Generalization	Nov 29, 2019	Domain AdaptationDomain Generalization	—Unverified
COSMIC: Data Efficient Instruction-tuning For Speech In-Context Learning	Nov 3, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
COSMOS: Cross-Modality Unsupervised Domain Adaptation for 3D Medical Image Segmentation based on Target-aware Domain Translation and Iterative Self-Training	Mar 30, 2022	Domain AdaptationImage Segmentation	—Unverified
Cost-Effective Incentive Allocation via Structured Counterfactual Inference	Feb 7, 2019	counterfactualCounterfactual Inference	—Unverified
Cost-Effective Training in Low-Resource Neural Machine Translation	Nov 16, 2021	Active LearningDomain Adaptation	—Unverified
Cost-Effective Training in Low-Resource Neural Machine Translation	Jan 14, 2022	Active LearningDomain Adaptation	—Unverified
Cost Weighting for Neural Machine Translation Domain Adaptation	Aug 1, 2017	Domain AdaptationMachine Translation	—Unverified
Co-Training for Domain Adaptation	Dec 1, 2011	Domain Adaptation	—Unverified
Co-training for On-board Deep Object Detection	Aug 12, 2020	Domain AdaptationObject	—Unverified
COT: Unsupervised Domain Adaptation With Clustering and Optimal Transport	Jan 1, 2023	ClusteringDomain Adaptation	—Unverified

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All datasets Office-31 SYNTHIA-to-Cityscapes GTA5 to Cityscapes Office-Home VisDA2017 ImageCLEF-DA Cityscapes to ACDC MNIST-to-USPS SVHN-to-MNIST USPS-to-MNIST SVNH-to-MNIST MoLane

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Average Accuracy	96	—	Unverified
2	PMTrans	Average Accuracy	95.3	—	Unverified
3	CMKD	Average Accuracy	94.4	—	Unverified
4	SSRT-B (ours)	Average Accuracy	93.5	—	Unverified
5	CDTrans	Average Accuracy	92.6	—	Unverified
6	CoVi	Average Accuracy	91.8	—	Unverified
7	GSDE	Average Accuracy	91.7	—	Unverified
8	FixBi	Average Accuracy	91.4	—	Unverified
9	Contrastive Adaptation Network	Average Accuracy	90.6	—	Unverified
10	BIWAA	Average Accuracy	90.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	78.1	—	Unverified
2	ILM-ASSL	mIoU	76.6	—	Unverified
3	DCF	mIoU	69.3	—	Unverified
4	HRDA+PiPa	mIoU	68.2	—	Unverified
5	MIC	mIoU	67.3	—	Unverified
6	FREDOM - Transformer	mIoU	67	—	Unverified
7	HRDA	mIoU	65.8	—	Unverified
8	SePiCo	mIoU	64.3	—	Unverified
9	MIC + Guidance Training	mIoU	63.8	—	Unverified
10	DAFormer + ProCST	mIoU	61.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	77.8	—	Unverified
2	DCF	mIoU	77.7	—	Unverified
3	ILM-ASSL	mIoU	76.1	—	Unverified
4	MIC	mIoU	75.9	—	Unverified
5	HRDA+PiPa	mIoU	75.6	—	Unverified
6	HRDA	mIoU	73.8	—	Unverified
7	FREDOM - Transformer	mIoU	73.6	—	Unverified
8	HALO	mIoU	73.3	—	Unverified
9	SePiCo	mIoU	70.3	—	Unverified
10	DAFormer + ProCST	mIoU	69.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SWG	Accuracy	92.3	—	Unverified
2	RCL	Accuracy	90	—	Unverified
3	PGA (ViT-L/14)	Accuracy	89.4	—	Unverified
4	PMTrans	Accuracy	89	—	Unverified
5	CMKD	Accuracy	89	—	Unverified
6	MIC	Accuracy	86.2	—	Unverified
7	PGA (ViT-B/16)	Accuracy	85.1	—	Unverified
8	ELS	Accuracy	84.6	—	Unverified
9	SDAT (ViT-B/16)	Accuracy	84.3	—	Unverified
10	CDTrans (DeiT-B)	Accuracy	80.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Accuracy	93.8	—	Unverified
2	RCL	Accuracy	93.2	—	Unverified
3	MIC	Accuracy	92.8	—	Unverified
4	SWG	Accuracy	92.7	—	Unverified
5	CMKD	Accuracy	91.8	—	Unverified
6	DePT	Accuracy	90.7	—	Unverified
7	SDAT(ViT)	Accuracy	89.8	—	Unverified
8	SFDA2++	Accuracy	89.6	—	Unverified
9	PMtrans	Accuracy	88.8	—	Unverified
10	CoVi	Accuracy	88.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CMKD	Accuracy	94.3	—	Unverified
2	MCC+NWD	Accuracy	90.7	—	Unverified
3	GLOT-DR	Accuracy	90.4	—	Unverified
4	SPL	Accuracy	90.3	—	Unverified
5	DFA-SAFN	Accuracy	90.2	—	Unverified
6	DADA	Accuracy	89.3	—	Unverified
7	DFA-ENT	Accuracy	89.1	—	Unverified
8	MEDM	Accuracy	88.9	—	Unverified
9	DDA	Accuracy	88.9	—	Unverified
10	IAFN+ENT	Accuracy	88.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SoRA	mIoU	78.8	—	Unverified
2	Rein	mIoU	77.6	—	Unverified
3	CoDA	mIoU	72.6	—	Unverified
4	Refign (HRDA)	mIoU	72.1	—	Unverified
5	HALO	mIoU	71.9	—	Unverified
6	MIC	mIoU	70.4	—	Unverified
7	HRDA	mIoU	68	—	Unverified
8	Refign (DAFormer)	mIoU	65.5	—	Unverified
9	VBLC (DAFormer)	mIoU	64.2	—	Unverified
10	CMFormer	mIoU	60.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FACT	Accuracy	98.8	—	Unverified
2	FAMCD	Accuracy	98.72	—	Unverified
3	DFA-MCD	Accuracy	98.6	—	Unverified
4	Mean teacher	Accuracy	98.26	—	Unverified
5	DRANet	Accuracy	98.2	—	Unverified
6	SHOT	Accuracy	98	—	Unverified
7	DFA-ENT	Accuracy	97.9	—	Unverified
8	CyCleGAN (Light-weight Calibrator)	Accuracy	97.1	—	Unverified