prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the NAT-M1 model in the Neural Architecture Transfer paper on the Flowers-102 dataset? | Accuracy, FLOPS, PARAMS, Per-Class Accuracy |
What metrics were used to measure the CoNAL model in the Learning from Crowds by Modeling Common Confusions paper on the LabelMe dataset? | Test 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 Surrey ASL dataset? | Accuracy (%) |
What metrics were used to measure the NOAH-ViTB/16 model in the Neural Prompt Search paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the SwinTransformer model in the Swin Transformer: Hierarchical Vision Transformer using Shifted Windows paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the ViT-B/16 model in the An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the Bamboo-R50 model in the Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the Adapter-ViTB/16 model in the Parameter-Efficient Transfer Learning for NLP paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the CLIP-RN50 model in the Learning Transferable Visual Models From Natural Language Supervision paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the IG-1B model in the Billion-scale semi-supervised learning for image classification paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the BiT-M model in the Big Transfer (BiT): General Visual Representation Learning paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the DINO model in the Emerging Properties in Self-Supervised Vision Transformers paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the SwAV model in the Unsupervised Learning of Visual Features by Contrasting Cluster Assignments paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the ResNet-101 model in the Deep Residual Learning for Image Recognition paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the MEAL-V2 model in the MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the MoPro-V2 model in the MoPro: Webly Supervised Learning with Momentum Prototypes paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the EfficientNetB4 model in the EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the MoCoV2 model in the Momentum Contrast for Unsupervised Visual Representation Learning paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the ResNet-50 model in the Deep Residual Learning for Image Recognition paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the InceptionV4 model in the Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the MLP-Mixer model in the MLP-Mixer: An all-MLP Architecture for Vision paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the Manifold model in the Manifold Mixup: Better Representations by Interpolating Hidden States paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the CutMix model in the CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the ReLabel model in the Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the MAE model in the Masked Autoencoders Are Scalable Vision Learners paper on the OmniBenchmark dataset? | Average Top-1 Accuracy |
What metrics were used to measure the BeiT model in the BEiT: BERT Pre-Training of Image Transformers paper on the OmniBenchmark dataset? | Average Top-1 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 FMD (materials) dataset? | Accuracy (%) |
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 CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the DINOv2 (ViT-g/14, frozen model, linear eval) model in the DINOv2: Learning Robust Visual Features without Supervision paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, 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 CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
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 CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the CaiT-M-36 U 224 model in the Going deeper with Image Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the CvT-W24 model in the CvT: Introducing Convolutions to Vision Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the BiT-L (ResNet) model in the Big Transfer (BiT): General Visual Representation Learning paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ViT-B (attn fine-tune) model in the Three things everyone should know about Vision Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the Heinsen Routing + BEiT-large 16 224 model in the An Algorithm for Routing Vectors in Sequences paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the VIT-L/16 (Background, Spinal FC) model in the Reduction of Class Activation Uncertainty with Background Information paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ViT-B/16 (PUGD) model in the Perturbated Gradients Updating within Unit Space for Deep Learning paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
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 CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the CeiT-S (384 finetune resolution) model in the Incorporating Convolution Designs into Visual Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the AutoFormer-S | 384 model in the AutoFormer: Searching Transformers for Visual Recognition paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the TNT-B model in the Transformer in Transformer paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the DeiT-B model in the Training data-efficient image transformers & distillation through attention paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the EfficientNetV2-L model in the EfficientNetV2: Smaller Models and Faster Training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the LaNet model in the Sample-Efficient Neural Architecture Search by Learning Action Space for Monte Carlo Tree Search paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the CeiT-S model in the Incorporating Convolution Designs into Visual Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the GPIPE + transfer learning model in the GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the TResNet-XL model in the TResNet: High Performance GPU-Dedicated Architecture paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the GFNet-H-B model in the Global Filter Networks for Image Classification paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the EfficientNetV2-M model in the EfficientNetV2: Smaller Models and Faster Training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the BiT-M (ResNet) model in the Big Transfer (BiT): General Visual Representation Learning paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the EfficientNet-B7 model in the EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the PyramidNet-272, S=4 model in the Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ResMLP-24 model in the ResMLP: Feedforward networks for image classification with data-efficient training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the EfficientNetV2-S model in the EfficientNetV2: Smaller Models and Faster Training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the PyramidNet-272 (ASAM) model in the ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the PyramidNet + ShakeDrop + Fast AA + FMix model in the FMix: Enhancing Mixed Sample Data Augmentation paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the PyramidNet (SAM) model in the Sharpness-Aware Minimization for Efficiently Improving Generalization paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ConvMLP-M model in the ConvMLP: Hierarchical Convolutional MLPs for Vision paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ConvMLP-L model in the ConvMLP: Hierarchical Convolutional MLPs for Vision paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ViT-B/16- SAM model in the When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the DVT (T2T-ViT-24) model in the Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, 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 CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the CeiT-T model in the Incorporating Convolution Designs into Visual Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the NAT-M4 model in the Neural Architecture Transfer paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the WRN-40-10, S=4 model in the Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the WRN-28-10, S=4 model in the Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the Dynamics 2 model in the PSO-Convolutional Neural Networks with Heterogeneous Learning Rate paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the Shake-Shake 26 2x96d, S=4 model in the Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ResNet50 (A1) model in the ResNet strikes back: An improved training procedure in timm paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the PyramidNet+ShakeDrop (Fast AA) model in the Fast AutoAugment paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the NoisyDARTS-A-t model in the Noisy Differentiable Architecture Search paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the LeViT-192 model in the LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ResNet-152-SAM model in the When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ViT-S/16- SAM model in the When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, 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 CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the NAT-M3 model in the Neural Architecture Transfer paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the LeViT-256 model in the LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ResMLP-12 model in the ResMLP: Feedforward networks for image classification with data-efficient training paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the PyramidNet + AA (AMP) model in the Regularizing Neural Networks via Adversarial Model Perturbation paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the EnAET model in the EnAET: A Self-Trained framework for Semi-Supervised and Supervised Learning with Ensemble Transformations paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the LeViT-384 model in the LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ConvMLP-S model in the ConvMLP: Hierarchical Convolutional MLPs for Vision paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the MUXNet-m model in the MUXConv: Information Multiplexing in Convolutional Neural Networks paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the CCT-7/3x1* model in the Escaping the Big Data Paradigm with Compact Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the Proxyless-G + c/o model in the ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the NAT-M2 model in the Neural Architecture Transfer paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the WRN-28-10+AutoDropout+RandAugment model in the AutoDropout: Learning Dropout Patterns to Regularize Deep Networks paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the SENet + ShakeShake + Cutout model in the Squeeze-and-Excitation Networks paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the HCGNet-A3 model in the Gated Convolutional Networks with Hybrid Connectivity for Image Classification paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the Wide-ResNet-28-10 model in the Automatic Data Augmentation via Invariance-Constrained Learning paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ResNeXt-50 (AutoMix) model in the AutoMix: Unveiling the Power of Mixup for Stronger Classifiers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the ResNet-152x4-AGC (ImageNet-21K) model in the Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest Images paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the Mixer-B/16- SAM model in the When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the CCT-7/3x1+VTM model in the TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the WRN-28-10 model in the MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the HCGNet-A2 model in the Gated Convolutional Networks with Hybrid Connectivity for Image Classification paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the WRN + fixup init + mixup + cutout model in the Fixup Initialization: Residual Learning Without Normalization paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, 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 CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
What metrics were used to measure the NoisyDARTS-a model in the Noisy Differentiable Architecture Search paper on the CIFAR-10 dataset? | Percentage correct, PARAMS, Top-1 Accuracy, Parameters, Accuracy |
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