prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the ImageNet - 500 classes + 10 steps of 50 classes dataset? | Average Incremental Accuracy, Final Accuracy |
What metrics were used to measure the UCIR (NME)* model in the Learning a Unified Classifier Incrementally via Rebalancing paper on the ImageNet - 500 classes + 10 steps of 50 classes dataset? | Average Incremental Accuracy, Final Accuracy |
What metrics were used to measure the PPCA-CLIP model in the Scalable Learning with Incremental Probabilistic PCA paper on the ImageNet - 500 classes + 10 steps of 50 classes dataset? | Average Incremental Accuracy, Final Accuracy |
What metrics were used to measure the MRM model in the MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition paper on the MLT17 dataset? | Acc |
What metrics were used to measure the TCIL model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR100-B0(10steps of 10 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the TCIL-Lite model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR100-B0(10steps of 10 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER(ResNet-18) model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the CIFAR100-B0(10steps of 10 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the CIFAR100-B0(10steps of 10 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the Coil model in the Co-Transport for Class-Incremental Learning paper on the CIFAR100-B0(10steps of 10 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the kNN-CLIP model in the Revisiting a kNN-based Image Classification System with High-capacity Storage paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the DyTox model in the DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the DER w/o Pruning model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the RMM (ResNet-18) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the DER model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the WA model in the Maintaining Discrimination and Fairness in Class Incremental Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the iCaRL model in the iCaRL: Incremental Classifier and Representation Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the BiC model in the Large Scale Incremental Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the E2E model in the End-to-End Incremental Learning paper on the ImageNet - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the FeTrIL model in the FeTrIL: Feature Translation for Exemplar-Free Class-Incremental Learning paper on the CIFAR-100 - 40 classes + 60 steps of 1 class (Exemplar-free) dataset? | Average Incremental Accuracy |
What metrics were used to measure the D3Former model in the D3Former: Debiased Dual Distilled Transformer for Incremental Learning paper on the CIFAR-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the RMM (Modified ResNet-32) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the CIFAR-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the CIFAR-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the CIFAR-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the BiC model in the Large Scale Incremental Learning paper on the CIFAR-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the kNN-CLIP model in the Revisiting a kNN-based Image Classification System with High-capacity Storage paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the RMM (ResNet-18) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the TCIL model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the TCIL-Lite model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the DER w/o Pruning model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the DyTox model in the DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the DER model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the WA model in the Maintaining Discrimination and Fairness in Class Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the BiC model in the Large Scale Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the E2E model in the End-to-End Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the RPSNet model in the An Adaptive Random Path Selection Approach for Incremental Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the iCaRL model in the iCaRL: Incremental Classifier and Representation Learning paper on the ImageNet100 - 10 steps dataset? | Average Incremental Accuracy, Final Accuracy, Average Incremental Accuracy Top-5, Final Accuracy Top-5, # M Params |
What metrics were used to measure the TCIL model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 2 steps of 25 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the TCIL-Lite model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 2 steps of 25 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER
(w/o P) model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 2 steps of 25 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the iCaRL model in the iCaRL: Incremental Classifier and Representation Learning paper on the CIFAR-100 - 50 classes + 2 steps of 25 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the PPCA-CLIP model in the Scalable Learning with Incremental Probabilistic PCA paper on the ImageNet-10k - 5225 classes + 5 steps of 1045 classes dataset? | Final Accuracy |
What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the ImageNet-100 - 50 classes + 50 steps of 1 class dataset? | Average Incremental Accuracy |
What metrics were used to measure the BiC model in the Large Scale Incremental Learning paper on the ImageNet-100 - 50 classes + 50 steps of 1 class dataset? | Average Incremental Accuracy |
What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the CIFAR-100 - 50 classes + 50 steps of 1 class dataset? | Average Incremental Accuracy |
What metrics were used to measure the BiC model in the Large Scale Incremental Learning paper on the CIFAR-100 - 50 classes + 50 steps of 1 class dataset? | Average Incremental Accuracy |
What metrics were used to measure the TCIL model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the TCIL-Lite model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER(w/o P) model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the BiC model in the Large Scale Incremental Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the WA model in the Maintaining Discrimination and Fairness in Class Incremental Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the iCaRL model in the iCaRL: Incremental Classifier and Representation Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the RPSNet model in the An Adaptive Random Path Selection Approach for Incremental Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the UCIR model in the Learning a Unified Classifier Incrementally via Rebalancing paper on the CIFAR-100-B0(5steps of 20 classes) dataset? | Average Incremental Accuracy |
What metrics were used to measure the TCIL model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the TCIL-Lite model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER(Standard ResNet-18) model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the D3Former model in the D3Former: Debiased Dual Distilled Transformer for Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the RMM (Modified ResNet-32) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER(Modified ResNet-32） model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the CCIL-SD model in the Essentials for Class Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the PODNet (CNN) model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the UCIR (CNN)* model in the Learning a Unified Classifier Incrementally via Rebalancing paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the UCIR (NME)* model in the Learning a Unified Classifier Incrementally via Rebalancing paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the BiC model in the Large Scale Incremental Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the iCaRL* model in the iCaRL: Incremental Classifier and Representation Learning paper on the CIFAR-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER(ResNet-18) model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the CIFAR100B050S(2ClassesPerStep) dataset? | Average Incremental Accuracy |
What metrics were used to measure the RMM (ResNet-18) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the ImageNet-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the ImageNet-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the ImageNet-100 - 50 classes + 25 steps of 2 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the RMM (ResNet-18) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the ImageNet-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the ImageNet-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the ImageNet-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the CCIL-SD model in the Essentials for Class Incremental Learning paper on the ImageNet-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the ImageNet-100 - 50 classes + 10 steps of 5 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the ImageNet100 - 20 steps dataset? | Average Incremental Accuracy |
What metrics were used to measure the RMM (ResNet-18) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the ImageNet - 500 classes + 5 steps of 100 classes dataset? | Average Incremental Accuracy, Final Accuracy |
What metrics were used to measure the CCIL-SD model in the Essentials for Class Incremental Learning paper on the ImageNet - 500 classes + 5 steps of 100 classes dataset? | Average Incremental Accuracy, Final Accuracy |
What metrics were used to measure the PODNet model in the PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning paper on the ImageNet - 500 classes + 5 steps of 100 classes dataset? | Average Incremental Accuracy, Final Accuracy |
What metrics were used to measure the PPCA-CLIP model in the Scalable Learning with Incremental Probabilistic PCA paper on the ImageNet - 500 classes + 5 steps of 100 classes dataset? | Average Incremental Accuracy, Final Accuracy |
What metrics were used to measure the TCIL-Lite model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR100B020Step(5ClassesPerStep) dataset? | Average Incremental Accuracy |
What metrics were used to measure the TCIL model in the Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning paper on the CIFAR100B020Step(5ClassesPerStep) dataset? | Average Incremental Accuracy |
What metrics were used to measure the DER(ResNet-18) model in the DER: Dynamically Expandable Representation for Class Incremental Learning paper on the CIFAR100B020Step(5ClassesPerStep) dataset? | Average Incremental Accuracy |
What metrics were used to measure the FOSTER model in the FOSTER: Feature Boosting and Compression for Class-Incremental Learning paper on the CIFAR100B020Step(5ClassesPerStep) dataset? | Average Incremental Accuracy |
What metrics were used to measure the RMM (ResNet-18) model in the RMM: Reinforced Memory Management for Class-Incremental Learning paper on the ImageNet - 500 classes + 25 steps of 20 classes dataset? | Average Incremental Accuracy |
What metrics were used to measure the Ours model in the Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation paper on the ISPRS dataset? | Average F1 |
What metrics were used to measure the Critical Points++&EPiC(RPC) model in the Critical Points ++: An Agile Point Cloud Importance Measure for Robust Classification, Adversarial Defense and Explainable AI paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the Critical Points++&EPiC(DGCNN) model in the Critical Points ++: An Agile Point Cloud Importance Measure for Robust Classification, Adversarial Defense and Explainable AI paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the Critical Points++&EPiC(GDANet) model in the Critical Points ++: An Agile Point Cloud Importance Measure for Robust Classification, Adversarial Defense and Explainable AI paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the EPiC (PCT+WOLFMix) model in the EPiC: Ensemble of Partial Point Clouds for Robust Classification paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the EPiC (DGCNN+WOLFMix) model in the EPiC: Ensemble of Partial Point Clouds for Robust Classification paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the EPiC(GDANet+WOLFMix) model in the EPiC: Ensemble of Partial Point Clouds for Robust Classification paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the WOLFMix (GDANet) model in the Benchmarking and Analyzing Point Cloud Classification under Corruptions paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the WOLFMix (DGCNN) model in the Benchmarking and Analyzing Point Cloud Classification under Corruptions paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the WOLFMix (RPC) model in the Benchmarking and Analyzing Point Cloud Classification under Corruptions paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the RSMix (DGCNN) model in the Regularization Strategy for Point Cloud via Rigidly Mixed Sample paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
What metrics were used to measure the PointWOLF (DGCNN) model in the Point Cloud Augmentation with Weighted Local Transformations paper on the PointCloud-C dataset? | mean Corruption Error (mCE) |
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