prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
|---|---|
What metrics were used to measure the NCE+MAE (ResNet-50) model in the Normalized Loss Functions for Deep Learning with Noisy Labels paper on the mini WebVision 1.0 dataset? | Top-1 Accuracy, Top-5 Accuracy, ImageNet Top-1 Accuracy, ImageNet Top-5 Accuracy |
What metrics were used to measure the CDR (Inception-ResNet-v2) model in the Robust early-learning: Hindering the memorization of noisy labels paper on the mini WebVision 1.0 dataset? | Top-1 Accuracy, Top-5 Accuracy, ImageNet Top-1 Accuracy, ImageNet Top-5 Accuracy |
What metrics were used to measure the SSR model in the SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise paper on the CIFAR-10 (with noisy labels) dataset? | Accuracy (under 20% Sym. label noise), Accuracy (under 50% Sym. label noise), Accuracy (under 80% Sym. label noise), Accuracy (under 90% Sym. label noise), Accuracy (under 95% Sym. label noise) |
What metrics were used to measure the C2D (ELR+ with SimCLR, ResNet-34) model in the Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels paper on the CIFAR-10 (with noisy labels) dataset? | Accuracy (under 20% Sym. label noise), Accuracy (under 50% Sym. label noise), Accuracy (under 80% Sym. label noise), Accuracy (under 90% Sym. label noise), Accuracy (under 95% Sym. label noise) |
What metrics were used to measure the PGDF (ResNet-18) model in the Sample Prior Guided Robust Model Learning to Suppress Noisy Labels paper on the CIFAR-10 (with noisy labels) dataset? | Accuracy (under 20% Sym. label noise), Accuracy (under 50% Sym. label noise), Accuracy (under 80% Sym. label noise), Accuracy (under 90% Sym. label noise), Accuracy (under 95% Sym. label noise) |
What metrics were used to measure the C2D (DivideMix with SimCLR, ResNet-18) model in the Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels paper on the CIFAR-10 (with noisy labels) dataset? | Accuracy (under 20% Sym. label noise), Accuracy (under 50% Sym. label noise), Accuracy (under 80% Sym. label noise), Accuracy (under 90% Sym. label noise), Accuracy (under 95% Sym. label noise) |
What metrics were used to measure the Heinsen Routing model in the An Algorithm for Routing Capsules in All Domains paper on the smallNORB dataset? | Classification Error |
What metrics were used to measure the Efficient-CapsNet model in the Efficient-CapsNet: Capsule Network with Self-Attention Routing paper on the smallNORB dataset? | Classification Error |
What metrics were used to measure the VB-Routing model in the Capsule Routing via Variational Bayes paper on the smallNORB dataset? | Classification Error |
What metrics were used to measure the Matrix-CapsNet with EM routing model in the Matrix capsules with EM routing paper on the smallNORB dataset? | Classification Error |
What metrics were used to measure the FRMS model in the Fast Dynamic Routing Based on Weighted Kernel Density Estimation paper on the smallNORB dataset? | Classification Error |
What metrics were used to measure the CapsNet model in the Dynamic Routing Between Capsules paper on the smallNORB dataset? | Classification Error |
What metrics were used to measure the DCNet model in the Dense and Diverse Capsule Networks: Making the Capsules Learn Better paper on the smallNORB dataset? | Classification Error |
What metrics were used to measure the InstanceGM-SS model in the Instance-Dependent Noisy Label Learning via Graphical Modelling paper on the Red MiniImageNet 60% label noise dataset? | Accuracy |
What metrics were used to measure the PropMix model in the PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels paper on the Red MiniImageNet 60% label noise dataset? | Accuracy |
What metrics were used to measure the InstanceGM model in the Instance-Dependent Noisy Label Learning via Graphical Modelling paper on the Red MiniImageNet 60% label noise dataset? | Accuracy |
What metrics were used to measure the FaMUS model in the Faster Meta Update Strategy for Noise-Robust Deep Learning paper on the Red MiniImageNet 60% label noise dataset? | Accuracy |
What metrics were used to measure the ResNet-18 model in the Reduction of Class Activation Uncertainty with Background Information paper on the EMNIST-Byclass dataset? | Accuracy |
What metrics were used to measure the WaveMixLite-128/7 model in the WaveMix: A Resource-efficient Neural Network for Image Analysis paper on the EMNIST-Byclass dataset? | Accuracy |
What metrics were used to measure the FaMUS model in the Faster Meta Update Strategy for Noise-Robust Deep Learning paper on the CIFAR-10, 40% Symmetric Noise dataset? | Percentage correct |
What metrics were used to measure the MentorMix model in the Faster Meta Update Strategy for Noise-Robust Deep Learning paper on the CIFAR-10, 40% Symmetric Noise dataset? | Percentage correct |
What metrics were used to measure the Astroformer model in the Astroformer: More Data Might not be all you need for Classification paper on the Galaxy10 DECals dataset? | Top-1 Accuracy (%) |
What metrics were used to measure the NCR (ResNet-18) model in the Learning with Neighbor Consistency for Noisy Labels paper on the Red MiniImageNet 80% label noise dataset? | Accuracy |
What metrics were used to measure the InstanceGM-SS model in the Instance-Dependent Noisy Label Learning via Graphical Modelling paper on the Red MiniImageNet 80% label noise dataset? | Accuracy |
What metrics were used to measure the PropMix model in the PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels paper on the Red MiniImageNet 80% label noise dataset? | Accuracy |
What metrics were used to measure the InstanceGM model in the Instance-Dependent Noisy Label Learning via Graphical Modelling paper on the Red MiniImageNet 80% label noise dataset? | Accuracy |
What metrics were used to measure the FaMUS model in the Faster Meta Update Strategy for Noise-Robust Deep Learning paper on the Red MiniImageNet 80% label noise dataset? | Accuracy |
What metrics were used to measure the CurriculumNet model in the CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the Forward model in the Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the CleanNet w_soft model in the CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the EMLC (k=1) model in the Enhanced Meta Label Correction for Coping with Label Corruption paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the DMLP-DivideMix model in the Learning from Noisy Labels with Decoupled Meta Label Purifier paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the FasTEN model in the Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the PUDistill model in the Training Classifiers that are Universally Robust to All Label Noise Levels paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the L2B (ResNet-18) model in the Learning to Bootstrap for Combating Label Noise paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the MLC model in the Meta Label Correction for Noisy Label Learning paper on the Clothing1M (using clean data) dataset? | Accuracy |
What metrics were used to measure the PDO-eConv (ours) model in the PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions paper on the MNIST-rot-12k (DA) dataset? | Test Error |
What metrics were used to measure the ResNet-50 + UDA+AutoDropout model in the AutoDropout: Learning Dropout Patterns to Regularize Deep Networks paper on the ImageNet-10 dataset? | Top 1 Accuracy |
What metrics were used to measure the pFedBreD_ns_mg model in the Personalized Federated Learning with Hidden Information on Personalized Prior paper on the FEMNIST dataset? | Accuracy |
What metrics were used to measure the RADAM (ConvNeXt-L) model in the RADAM: Texture Recognition through Randomized Aggregated Encoding of Deep Activation Maps paper on the DTD dataset? | Accuracy |
What metrics were used to measure the µ2Net+ (ViT-L/16) model in the A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems paper on the DTD dataset? | Accuracy |
What metrics were used to measure the Bamboo (ViT-B/16) model in the Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy paper on the DTD dataset? | Accuracy |
What metrics were used to measure the µ2Net (ViT-L/16) model in the An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems paper on the DTD dataset? | Accuracy |
What metrics were used to measure the SEER (RegNet10B - linear eval) model in the Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision paper on the DTD dataset? | Accuracy |
What metrics were used to measure the Inceptionv4 model in the Non-binary deep transfer learning for image classification paper on the DTD dataset? | Accuracy |
What metrics were used to measure the TWIST (ResNet-50) model in the Self-Supervised Learning by Estimating Twin Class Distributions paper on the DTD dataset? | Accuracy |
What metrics were used to measure the TransBoost-ResNet50 model in the TransBoost: Improving the Best ImageNet Performance using Deep Transduction paper on the DTD dataset? | Accuracy |
What metrics were used to measure the NNCLR model in the With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations paper on the DTD dataset? | Accuracy |
What metrics were used to measure the Inceptionv4 (random initialization) model in the Non-binary deep transfer learning for image classification paper on the DTD dataset? | Accuracy |
What metrics were used to measure the SimCLR model in the Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style paper on the Causal3DIdent dataset? | Accuracy |
What metrics were used to measure the Barlow Twins model in the Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style paper on the Causal3DIdent dataset? | Accuracy |
What metrics were used to measure the Inception-v3 model in the Class Distance Weighted Cross-Entropy Loss for Ulcerative Colitis Severity Estimation paper on the LIMUC dataset? | Quadratic Weighted Kappa |
What metrics were used to measure the DenseNet121 model in the Improving the Computer-Aided Estimation of Ulcerative Colitis Severity According to Mayo Endoscopic Score by Using Regression-Based Deep Learning paper on the LIMUC dataset? | Quadratic Weighted Kappa |
What metrics were used to measure the WaveMixLite-112/16 model in the WaveMix: A Resource-efficient Neural Network for Image Analysis paper on the EMNIST-Digits dataset? | Accuracy (%) |
What metrics were used to measure the µ2Net (ViT-L/16) model in the An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems paper on the EMNIST-Digits dataset? | Accuracy (%) |
What metrics were used to measure the VGG-5(Spinal FC) model in the SpinalNet: Deep Neural Network with Gradual Input paper on the EMNIST-Digits dataset? | Accuracy (%) |
What metrics were used to measure the OptConv+Log+Perc model in the Efficient Neural Vision Systems Based on Convolutional Image Acquisition paper on the EMNIST-Digits dataset? | Accuracy (%) |
What metrics were used to measure the SVM classifier model in the Handwritten digit and letter recognition using hybrid dwt-dct with knn and svm classifier paper on the EMNIST-Digits dataset? | Accuracy (%) |
What metrics were used to measure the OPIUM Classifier model in the EMNIST: an extension of MNIST to handwritten letters paper on the EMNIST-Digits dataset? | Accuracy (%) |
What metrics were used to measure the Linear Classifier model in the EMNIST: an extension of MNIST to handwritten letters paper on the EMNIST-Digits dataset? | Accuracy (%) |
What metrics were used to measure the InternImage-H model in the InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions paper on the Places365 dataset? | Top 1 Accuracy |
What metrics were used to measure the MixMIM-L model in the MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers paper on the Places365 dataset? | Top 1 Accuracy |
What metrics were used to measure the µ2Net+ (ViT-L/16) model in the A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems paper on the Places365 dataset? | Top 1 Accuracy |
What metrics were used to measure the MixMIM-B model in the MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers paper on the Places365 dataset? | Top 1 Accuracy |
What metrics were used to measure the FaMUS model in the Faster Meta Update Strategy for Noise-Robust Deep Learning paper on the CIFAR-100, 40% Symmetric Noise dataset? | Percentage correct |
What metrics were used to measure the MentorMix model in the Faster Meta Update Strategy for Noise-Robust Deep Learning paper on the CIFAR-100, 40% Symmetric Noise dataset? | Percentage correct |
What metrics were used to measure the TransBoost-ResNet50 model in the TransBoost: Improving the Best ImageNet Performance using Deep Transduction paper on the FGVC Aircraft dataset? | Accuracy |
What metrics were used to measure the Bamboo (ViTB/16) model in the Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy paper on the Food-101 dataset? | Accuracy (%), Accuracy |
What metrics were used to measure the SEER (RegNet10B - linear eval) model in the Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision paper on the Food-101 dataset? | Accuracy (%), Accuracy |
What metrics were used to measure the TWIST (ResNet-50) model in the Self-Supervised Learning by Estimating Twin Class Distributions paper on the Food-101 dataset? | Accuracy (%), Accuracy |
What metrics were used to measure the TransBoost-ResNet50 model in the TransBoost: Improving the Best ImageNet Performance using Deep Transduction paper on the Food-101 dataset? | Accuracy (%), Accuracy |
What metrics were used to measure the NNCLR model in the With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations paper on the Food-101 dataset? | Accuracy (%), Accuracy |
What metrics were used to measure the Inception V3 model in the Image and Text fusion for UPMC Food-101 \\using BERT and CNNs paper on the Food-101 dataset? | Accuracy (%), Accuracy |
What metrics were used to measure the efficient adaptive ensembling model in the Efficient Adaptive Ensembling for Image Classification paper on the Food-101 dataset? | Accuracy (%), Accuracy |
What metrics were used to measure the UPANets model in the UPANets: Learning from the Universal Pixel Attention Networks paper on the Tiny-ImageNet dataset? | Top 1 Accuracy, Top-1 Accuracy |
What metrics were used to measure the PreActResNet18 model in the Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup paper on the Tiny-ImageNet dataset? | Top 1 Accuracy, Top-1 Accuracy |
What metrics were used to measure the DLME (ResNet-18, linear) model in the DLME: Deep Local-flatness Manifold Embedding paper on the Tiny-ImageNet dataset? | Top 1 Accuracy, Top-1 Accuracy |
What metrics were used to measure the MMA-CCT-7/3x2 model in the Multi-manifold Attention for Vision Transformers paper on the Tiny-ImageNet dataset? | Top 1 Accuracy, Top-1 Accuracy |
What metrics were used to measure the E2E-3M model in the Rethinking Recurrent Neural Networks and Other Improvements for Image Classification paper on the iCassava'19 dataset? | Top-1 Accuracy |
What metrics were used to measure the Baseline (ViT-G/14) model in the Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the ViTAE-H
(MAE, 512) model in the ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the Model soups (ViT-G/14) model in the Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the Meta Pseudo Labels (EfficientNet-B6-Wide) model in the Meta Pseudo Labels paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the TokenLearner L/8 (24+11) model in the TokenLearner: What Can 8 Learned Tokens Do for Images and Videos? paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the Model soups (BASIC-L) model in the Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the Meta Pseudo Labels (EfficientNet-L2) model in the Meta Pseudo Labels paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the MAWS (ViT-2B) model in the The effectiveness of MAE pre-pretraining for billion-scale pretraining paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the FixEfficientNet-L2 model in the Fixing the train-test resolution discrepancy: FixEfficientNet paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the ViT-G/14 model in the Scaling Vision Transformers paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the ViT-H/14 model in the An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the SWAG (RegNetY 128GF) model in the Revisiting Weakly Supervised Pre-Training of Visual Perception Models paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the VOLO-D5 model in the VOLO: Vision Outlooker for Visual Recognition paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the CvT-W24 (384 res, ImageNet-22k pretrain) model in the CvT: Introducing Convolutions to Vision Transformers paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the EfficientNet-L2 model in the Self-training with Noisy Student improves ImageNet classification paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the ViT-L/16 model in the An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the BiT-L model in the Big Transfer (BiT): General Visual Representation Learning paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the VOLO-D4 model in the VOLO: Vision Outlooker for Visual Recognition paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the CAIT-M36-448 model in the Going deeper with Image Transformers paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the Mixer-H/14- 448 (JFT-300M pre-train) model in the MLP-Mixer: An all-MLP Architecture for Vision paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
What metrics were used to measure the FixEfficientNet-B8 model in the Fixing the train-test resolution discrepancy: FixEfficientNet paper on the ImageNet ReaL dataset? | Accuracy, Params, Top 1 Accuracy, Number of params |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.