prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the BALMS model in the Balanced Meta-Softmax for Long-Tailed Visual Recognition paper on the Places-LT dataset? | Top-1 Accuracy, Top 1 Accuracy |
What metrics were used to measure the smDRAGON model in the From Generalized zero-shot learning to long-tail with class descriptors paper on the Places-LT dataset? | Top-1 Accuracy, Top 1 Accuracy |
What metrics were used to measure the CB LWS model in the Decoupling Representation and Classifier for Long-Tailed Recognition paper on the Places-LT dataset? | Top-1 Accuracy, Top 1 Accuracy |
What metrics were used to measure the Online Feature Augmentation model in the Feature Space Augmentation for Long-Tailed Data paper on the Places-LT dataset? | Top-1 Accuracy, Top 1 Accuracy |
What metrics were used to measure the LFME + OLTR model in the Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification paper on the Places-LT dataset? | Top-1 Accuracy, Top 1 Accuracy |
What metrics were used to measure the OLTR model in the Large-Scale Long-Tailed Recognition in an Open World paper on the Places-LT dataset? | Top-1 Accuracy, Top 1 Accuracy |
What metrics were used to measure the Domain Adaptation model in the Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective paper on the Places-LT dataset? | Top-1 Accuracy, Top 1 Accuracy |
What metrics were used to measure the GML (ViT-B-16) model in the Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the VL-LTR (ViT-B-16) model in the VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the PEL (ViT-B/16) model in the Parameter-Efficient Long-Tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the RAC (ViT-B-16) model in the Retrieval Augmented Classification for Long-Tail Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the GPaCo (2-R152) model in the Generalized Parametric Contrastive Learning paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the GPaCo (ResNet-152) model in the Generalized Parametric Contrastive Learning paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the TADE(ResNet-152) model in the Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the MDCS(Resnet50) model in the MDCS: More Diverse Experts with Consistency Self-distillation for Long-tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the GPaCo (ResNet-50) model in the Generalized Parametric Contrastive Learning paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the CBD-ENS (ResNet-101) model in the Class-Balanced Distillation for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the PaCo(ResNet-152) model in the Parametric Contrastive Learning paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the VL-LTR (ResNet-50) model in the VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the GML (ResNet-50) model in the Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the NCL(ResNet-50) model in the Nested Collaborative Learning for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the BatchFormer(ResNet-50, RIDE) model in the BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the CBD-ENS (ResNet-50) model in the Class-Balanced Distillation for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the RIDE-DiVE model in the Distilling Virtual Examples for Long-tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the TADE model in the Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the ResLT(3 experts) model in the ResLT: Residual Learning for Long-tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the RIDE model in the Long-tailed Recognition by Routing Diverse Distribution-Aware Experts paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the BCL(ResNet-50) model in the Balanced Contrastive Learning for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the DiVE model in the Distilling Virtual Examples for Long-tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the MiSLAS model in the Improving Calibration for Long-Tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the DisAlign model in the Distribution Alignment: A Unified Framework for Long-tail Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the LDAM-DRS-RSG model in the RSG: A Simple but Effective Module for Learning Imbalanced Datasets paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the IEM model in the Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the LTR-weight-balancing(ResNet-50) model in the Long-Tailed Recognition via Weight Balancing paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the LDAM + DRW + SAM model in the Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the LADE model in the Disentangling Label Distribution for Long-tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the TSC(ResNet-50) model in the Targeted Supervised Contrastive Learning for Long-Tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the CB-LWS model in the Decoupling Representation and Classifier for Long-Tailed Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the MetaSAug model in the MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the cRT + SSP model in the Rethinking the Value of Labels for Improving Class-Imbalanced Learning paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the Hybrid-PSC model in the Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the CE-DRW-IC model in the Posterior Re-calibration for Imbalanced Datasets paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the Domain Adaptation model in the Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the Online Feature Augmentation model in the Feature Space Augmentation for Long-Tailed Data paper on the iNaturalist 2018 dataset? | Top-1 Accuracy |
What metrics were used to measure the Decoupling (cRT) model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Reweighted LDAM-DRW model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Class-balanced LDAM-DRW model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Reweighted LDAM model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Class-Balanced Softmax model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Reweighted Softmax model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Class-balanced LDAM model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Class-Balanced Focal Loss model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Decoupling (tau-norm) model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Reweighted Focal Loss model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the LDAM model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Balanced-MixUp model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Focal Loss model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the MixUp model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the Softmax model in the Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study paper on the NIH-CXR-LT dataset? | Balanced Accuracy |
What metrics were used to measure the LDAM + DRW + SAM model in the Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data paper on the CIFAR-10-LT (ρ=200) dataset? | Error Rate |
What metrics were used to measure the MetaSAug-LDAM model in the MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition paper on the CIFAR-10-LT (ρ=200) dataset? | Error Rate |
What metrics were used to measure the GLMC+MaxNorm (ResNet-32, channel x4) model in the Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the GLMC (ResNet-32, channel x4) model in the Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the 3LSSL model in the Delving Deep into Simplicity Bias for Long-Tailed Image Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ResCom model in the Rebalanced Siamese Contrastive Mining for Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the Balanced Softmax (BALMS) model in the Balanced Meta-Softmax for Long-Tailed Visual Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ViT-B + Bal-BCE model in the Learning Imbalanced Data with Vision Transformers paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the LCReg model in the Long-tailed Recognition by Learning from Latent Categories paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the BCL(ResNet-32) model in the Balanced Contrastive Learning for Long-Tailed Visual Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the Hybrid-SC model in the Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the LWS model in the Decoupling Representation and Classifier for Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the cRT model in the Decoupling Representation and Classifier for Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the PCL model in the Parametric Contrastive Learning paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the TADE model in the Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ViT-B + Bal-CE model in the Learning Imbalanced Data with Vision Transformers paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the Equalization Loss model in the Equalization Loss for Long-Tailed Object Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the MiSLAS model in the Improving Calibration for Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ViT-B + CB model in the Learning Imbalanced Data with Vision Transformers paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the De-C-TDE + Curvature Regularization model in the Curvature-Balanced Feature Manifold Learning for Long-Tailed Classification paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the L2A(S2) model in the Leveraging Angular Information Between Feature and Classifier for Long-tailed Learning: A Prediction Reformulation Approach paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ResLT model in the ResLT: Residual Learning for Long-tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the RIDE model in the Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ICCL model in the Improving Tail-Class Representation with Centroid Contrastive Learning paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the MetaSAug-LDAM model in the MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the UniMix+Bayias model in the Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ViT-B + CE model in the Learning Imbalanced Data with Vision Transformers paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the LDAM + DRW + SAM model in the Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the SAFA+LDAM-DRW (ResNeXt-29) model in the SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the GCLLoss model in the Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the LADE model in the Disentangling Label Distribution for Long-tailed Visual Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ELP model in the A Simple Episodic Linear Probe Improves Visual Recognition in the Wild paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the TSC model in the Targeted Supervised Contrastive Learning for Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ViT-B + LDAM model in the Learning Imbalanced Data with Vision Transformers paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the LDAM-DRW + SSP model in the Rethinking the Value of Labels for Improving Class-Imbalanced Learning paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the Causal Norm model in the Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the BBN model in the BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the smDRAGON model in the From Generalized zero-shot learning to long-tail with class descriptors paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the LDAM-DRW model in the Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the ELF&LDAM+DRW model in the ELF: An Early-Exiting Framework for Long-Tailed Classification paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the KCL model in the Exploring Balanced Feature Spaces for Representation Learning paper on the CIFAR-10-LT (ρ=10) dataset? | Error Rate |
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