prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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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-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the PC model in the Learning Prototype Classifiers for Long-Tailed Recognition paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the LTR-weight-balancing model in the Long-Tailed Recognition via Weight Balancing paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the GML (ResNet-32) model in the Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the Difficulty-Net model in the Difficulty-Net: Learning to Predict Difficulty for Long-Tailed Recognition paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the BCL+CUDA model in the CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the GLAG model in the Long-Tailed Classification with Gradual Balanced Loss and Adaptive Feature Generation paper on the CIFAR-100-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-100-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-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the DRO-LT model in the Distributional Robustness Loss for Long-tail Learning paper on the CIFAR-100-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-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the SMC model in the Supervised Contrastive Learning on Blended Images for Long-tailed Recognition paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
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 CIFAR-100-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-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the RIDE + CMO + Curvature Regularization model in the Curvature-Balanced Feature Manifold Learning for Long-Tailed Classification paper on the CIFAR-100-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-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the UniMix+Bayias (ResNet-32) model in the Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the CBD+TailCalibX model in the Feature Generation for Long-tail Classification paper on the CIFAR-100-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-100-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-100-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-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the CDB-loss model in the Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance paper on the CIFAR-100-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-100-LT (ρ=10) dataset? | Error Rate |
What metrics were used to measure the CE-DRW-IC model in the Posterior Re-calibration for Imbalanced Datasets paper on the CIFAR-100-LT (ρ=10) dataset? | Error Rate |
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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-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 MIMIC-CXR-LT dataset? | Balanced Accuracy |
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=100) dataset? | Error Rate |
What metrics were used to measure the GLMC + SAM model in the Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the LPT model in the LPT: Long-tailed Prompt Tuning for Image Classification paper on the CIFAR-10-LT (ρ=100) 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=100) dataset? | Error Rate |
What metrics were used to measure the OPeN (WideResNet-28-10) model in the Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the SimSiam+rwSAM model in the Self-supervised Learning is More Robust to Dataset Imbalance paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the NCL(ResNet32) model in the Nested Collaborative Learning for Long-Tailed Visual Recognition paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the NCL* + WGCC (ensemble) model in the Weight-guided class complementing for long-tailed image recognition paper on the CIFAR-10-LT (ρ=100) 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=100) dataset? | Error Rate |
What metrics were used to measure the GCL model in the Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the FBL (ResNet-32) model in the Feature-Balanced Loss for Long-Tailed Visual Recognition paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the VS + SAM model in the Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data paper on the CIFAR-10-LT (ρ=100) 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=100) dataset? | Error Rate |
What metrics were used to measure the ACE (4 experts) model in the ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot paper on the CIFAR-10-LT (ρ=100) 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=100) dataset? | Error Rate |
What metrics were used to measure the TLC (4 experts) model in the Trustworthy Long-Tailed Classification paper on the CIFAR-10-LT (ρ=100) 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=100) dataset? | Error Rate |
What metrics were used to measure the CE+DRS+GIT model in the Do Deep Networks Transfer Invariances Across Classes? paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the TSC(ResNet-32) model in the Targeted Supervised Contrastive Learning for Long-Tailed Recognition paper on the CIFAR-10-LT (ρ=100) 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=100) 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=100) 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=100) dataset? | Error Rate |
What metrics were used to measure the ETF Classifier + DR (Resnet) model in the Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? paper on the CIFAR-10-LT (ρ=100) dataset? | Error Rate |
What metrics were used to measure the OPeN (WideResNet-28-10) model in the Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images paper on the CelebA-5 dataset? | Error Rate |
What metrics were used to measure the Character-BERT+RS model in the Text Classification in the Wild: a Large-scale Long-tailed Name Normalization Dataset paper on the Lot-insts dataset? | Macro-F1 |
What metrics were used to measure the RIDE + IFL model in the Invariant Feature Learning for Generalized Long-Tailed Classification paper on the ImageNet-GLT dataset? | Accuracy |
What metrics were used to measure the RandAug + IFL model in the Invariant Feature Learning for Generalized Long-Tailed Classification paper on the ImageNet-GLT dataset? | Accuracy |
What metrics were used to measure the Logit-Adj + IFL model in the Invariant Feature Learning for Generalized Long-Tailed Classification paper on the ImageNet-GLT dataset? | Accuracy |
What metrics were used to measure the BLSoftmax + IFL model in the Invariant Feature Learning for Generalized Long-Tailed Classification paper on the ImageNet-GLT dataset? | Accuracy |
What metrics were used to measure the LDAM model in the Invariant Feature Learning for Generalized Long-Tailed Classification paper on the ImageNet-GLT dataset? | Accuracy |
What metrics were used to measure the cRT model in the Invariant Feature Learning for Generalized Long-Tailed Classification paper on the ImageNet-GLT dataset? | Accuracy |
What metrics were used to measure the MVCN model in the Better Generalized Few-Shot Learning Even Without Base Data paper on the CUB dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the CADA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the CUB dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the CA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the CUB dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the DA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the CUB dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the REVISE model in the Learning Robust Visual-Semantic Embeddings paper on the CUB dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the DRAGON model in the From Generalized zero-shot learning to long-tail with class descriptors paper on the SUN dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots) |
What metrics were used to measure the DA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the SUN dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots) |
What metrics were used to measure the CADA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the SUN dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots) |
What metrics were used to measure the CA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the SUN dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots) |
What metrics were used to measure the REVISE model in the Learning Robust Visual-Semantic Embeddings paper on the SUN dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots) |
What metrics were used to measure the MVCN model in the Better Generalized Few-Shot Learning Even Without Base Data paper on the AwA2 dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the CADA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the AwA2 dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the DA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the AwA2 dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the DRAGON model in the From Generalized zero-shot learning to long-tail with class descriptors paper on the AwA2 dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the CA-VAE model in the Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders paper on the AwA2 dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the REVISE model in the Learning Robust Visual-Semantic Embeddings paper on the AwA2 dataset? | Per-Class Accuracy (1-shot), Per-Class Accuracy (2-shots), Per-Class Accuracy (5-shots), Per-Class Accuracy (10-shots), Per-Class Accuracy (20-shots) |
What metrics were used to measure the BasicVSR++ model in the BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment paper on the MFQE v2 dataset? | Incremental PSNR, Parameters(M) |
What metrics were used to measure the S2SVR model in the Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration paper on the MFQE v2 dataset? | Incremental PSNR, Parameters(M) |
What metrics were used to measure the STDF model in the Spatio-temporal deformable convolution for compressed video quality enhancement paper on the MFQE v2 dataset? | Incremental PSNR, Parameters(M) |
What metrics were used to measure the EDVR model in the EDVR: Video Restoration with Enhanced Deformable Convolutional Networks paper on the MFQE v2 dataset? | Incremental PSNR, Parameters(M) |
What metrics were used to measure the MFQE 2.0 model in the MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video paper on the MFQE v2 dataset? | Incremental PSNR, Parameters(M) |
What metrics were used to measure the MFQE 1.0 model in the Multi-Frame Quality Enhancement for Compressed Video paper on the MFQE v2 dataset? | Incremental PSNR, Parameters(M) |
What metrics were used to measure the TransC (bern) model in the Differentiating Concepts and Instances for Knowledge Graph Embedding paper on the YAGO39K dataset? | Accuracy, F1-Score, Precision, Recall |
What metrics were used to measure the DS-UNet model in the Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction paper on the Burned Area Delineation from Satellite Imagery dataset? | RMSE |
What metrics were used to measure the VAST model in the VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset paper on the YouCook2 dataset? | text-to-video R@1, text-to-video R@5, text-to-video R@10, text-to-video Median Rank, text-to-video Mean Rank |
What metrics were used to measure the UniVL + MELTR model in the MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models paper on the YouCook2 dataset? | text-to-video R@1, text-to-video R@5, text-to-video R@10, text-to-video Median Rank, text-to-video Mean Rank |
What metrics were used to measure the VideoCLIP model in the VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding paper on the YouCook2 dataset? | text-to-video R@1, text-to-video R@5, text-to-video R@10, text-to-video Median Rank, text-to-video Mean Rank |
What metrics were used to measure the MDMMT-2 model in the MDMMT-2: Multidomain Multimodal Transformer for Video Retrieval, One More Step Towards Generalization paper on the YouCook2 dataset? | text-to-video R@1, text-to-video R@5, text-to-video R@10, text-to-video Median Rank, text-to-video Mean Rank |
What metrics were used to measure the TACo model in the TACo: Token-aware Cascade Contrastive Learning for Video-Text Alignment paper on the YouCook2 dataset? | text-to-video R@1, text-to-video R@5, text-to-video R@10, text-to-video Median Rank, text-to-video Mean Rank |
What metrics were used to measure the UniVL model in the UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation paper on the YouCook2 dataset? | text-to-video R@1, text-to-video R@5, text-to-video R@10, text-to-video Median Rank, text-to-video Mean Rank |
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