SOTAVerified

Domain Generalization

The idea of Domain Generalization is to learn from one or multiple training domains, to extract a domain-agnostic model which can be applied to an unseen domain

Source: Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning

Papers

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Showing 1551–1600 of 1751 papers

TitleStatusHype
Identifying Knowledge Editing Types in Large Language ModelsCode0
Beyond Interpretability: The Gains of Feature Monosemanticity on Model RobustnessCode0
Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensemblesCode0
Domain-agnostic Question-Answering with Adversarial TrainingCode0
How Does Distribution Matching Help Domain Generalization: An Information-theoretic AnalysisCode0
Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous DrivingCode0
On the challenges of detecting MCI using EEG in the wildCode0
Histopathological Image Analysis with Style-Augmented Feature Domain Mixing for Improved GeneralizationCode0
Benchmarking Domain Generalization Algorithms in Computational PathologyCode0
Slimmable Domain AdaptationCode0
BatStyler: Advancing Multi-category Style Generation for Source-free Domain GeneralizationCode0
On the Fly Neural Style Smoothing for Risk-Averse Domain GeneralizationCode0
Domain Adversarial Neural Networks for Domain Generalization: When It Works and How to ImproveCode0
Soft-Prompting with Graph-of-Thought for Multi-modal Representation LearningCode0
Barycentric-alignment and reconstruction loss minimization for domain generalizationCode0
Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous DomainsCode0
On the Interplay of Human-AI Alignment,Fairness, and Performance Trade-offs in Medical ImagingCode0
HeteroSwitch: Characterizing and Taming System-Induced Data Heterogeneity in Federated LearningCode0
Doge Tickets: Uncovering Domain-general Language Models by Playing Lottery TicketsCode0
On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean FunctionsCode0
On the Universal Truthfulness Hyperplane Inside LLMsCode0
Heterogeneous Domain Generalization via Domain MixupCode0
ConStyX: Content Style Augmentation for Generalizable Medical Image SegmentationCode0
HCDG: A Hierarchical Consistency Framework for Domain Generalization on Medical Image SegmentationCode0
DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen DatasetsCode0
Divergent Domains, Convergent Grading: Enhancing Generalization in Diabetic Retinopathy GradingCode0
Harmonization with Flow-based Causal InferenceCode0
OpenStance: Real-world Zero-shot Stance DetectionCode0
Distribution-aware Noisy-label Crack SegmentationCode0
GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm SegmentationCode0
Grounding Stylistic Domain Generalization with Quantitative Domain Shift Measures and Synthetic Scene ImagesCode0
Distillation-based fabric anomaly detectionCode0
Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and TasksCode0
OSLoPrompt: Bridging Low-Supervision Challenges and Open-Set Domain Generalization in CLIPCode0
Discriminative Radial Domain AdaptationCode0
Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL ParsingCode0
SSL-DG: Rethinking and Fusing Semi-supervised Learning and Domain Generalization in Medical Image SegmentationCode0
Out-of-Domain Generalization in Dynamical Systems ReconstructionCode0
Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain GeneralizationCode0
GRAIL: Graph Edit Distance and Node Alignment Using LLM-Generated CodeCode0
GOPro: Generate and Optimize Prompts in CLIP using Self-Supervised LearningCode0
Global-Local Regularization Via Distributional RobustnessCode0
Generalizing to Unseen Domains in Diabetic Retinopathy ClassificationCode0
Generalizing to Evolving Domains with Latent Structure-Aware Sequential AutoencoderCode0
Generalizing Across Domains via Cross-Gradient TrainingCode0
Generalizing Across Domains in Diabetic Retinopathy via Variational AutoencodersCode0
Back-to-Bones: Rediscovering the Role of Backbones in Domain GeneralizationCode0
GeneralizeFormer: Layer-Adaptive Model Generation across Test-Time Distribution ShiftsCode0
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain SchedulerCode0
Generalized Semantic Segmentation by Self-Supervised Source Domain Projection and Multi-Level Contrastive LearningCode0
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All datasetsPACSVizWiz-ClassificationImageNet-COffice-HomeImageNet-AImageNet-RDomainNetVLCSTerraIncognitaGTA-to-Avg(Cityscapes,BDD,Mapillary)ImageNet-SketchGTA5 to Cityscapes

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SIMPLE+Average Accuracy99—Unverified
2PromptStyler (CLIP, ViT-L/14)Average Accuracy98.6—Unverified
3GMDG (RegNetY-16GF, SWAD)Average Accuracy97.9—Unverified
4D-Triplet(RegNetY-16GF)Average Accuracy97.6—Unverified
5MoA (OpenCLIP, ViT-B/16)Average Accuracy97.4—Unverified
6GMDG (e RegNetY-16GF)Average Accuracy97.3—Unverified
7PromptStyler (CLIP, ViT-B/16)Average Accuracy97.2—Unverified
8SPG (CLIP, ViT-B/16)Average Accuracy97—Unverified
9CAR-FT (CLIP, ViT-B/16)Average Accuracy96.8—Unverified
10MIRO (RegNetY-16GF, SWAD)Average Accuracy96.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-8/B-224Accuracy - Clean Images450—Unverified
2VOLO-D5Accuracy - All Images57.2—Unverified
3ConvNeXt-BAccuracy - All Images53.5—Unverified
4ResNeXt-101 32x16dAccuracy - All Images51.7—Unverified
5EfficientNet-B8 (advprop+autoaug)Accuracy - All Images50.5—Unverified
6EfficientNet-B7 (advprop+autoaug)Accuracy - All Images49.7—Unverified
7EfficientNet-B6 (advprop+autoaug)Accuracy - All Images49.6—Unverified
8EfficientNet-B5 (advprop+autoaug)Accuracy - All Images49.1—Unverified
9ViT-16/L-224Accuracy - All Images49—Unverified
10ResNet-50 (gn)Accuracy - All Images48.9—Unverified