prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the NCBI_BERT(base) (P) model in the Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets paper on the BC5CDR-chemical dataset? | F1 |
What metrics were used to measure the KeBioLM model in the Improving Biomedical Pretrained Language Models with Knowledge paper on the BC5CDR-chemical dataset? | F1 |
What metrics were used to measure the BioMegatron model in the BioMegatron: Larger Biomedical Domain Language Model paper on the BC5CDR-chemical dataset? | F1 |
What metrics were used to measure the Att-BiLSTM-CRF model in the An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition paper on the BC5CDR-chemical dataset? | F1 |
What metrics were used to measure the Spark NLP model in the Biomedical Named Entity Recognition at Scale paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the aimped model in the paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BioKMNER + BioBERT model in the Improving Biomedical Named Entity Recognition with Syntactic Information paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the ConNER model in the Enhancing Label Consistency on Document-level Named Entity Recognition paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BioBERT model in the BioBERT: a pre-trained biomedical language representation model for biomedical text mining paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the SpanModel + SequenceLabelingModel model in the Comparing and combining some popular NER approaches on Biomedical tasks paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the SciFive-Base model in the SciFive: a text-to-text transformer model for biomedical literature paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BLSTM-CNN-Char (SparkNLP) model in the Biomedical Named Entity Recognition at Scale paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the KeBioLM model in the Improving Biomedical Pretrained Language Models with Knowledge paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the CL-KL model in the Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BioFLAIR model in the BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling Tasks paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BioLinkBERT (large) model in the LinkBERT: Pretraining Language Models with Document Links paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the CompactBioBERT model in the On the Effectiveness of Compact Biomedical Transformers paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the DistilBioBERT model in the On the Effectiveness of Compact Biomedical Transformers paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the RDANER model in the A Robust and Domain-Adaptive Approach for Low-Resource Named Entity Recognition paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the PubMedBERT uncased model in the Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BioMegatron BERT-cased model in the BioMegatron: Larger Biomedical Domain Language Model paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BioDistilBERT model in the On the Effectiveness of Compact Biomedical Transformers paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the ELECTRAMed model in the ELECTRAMed: a new pre-trained language representation model for biomedical NLP paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BioMobileBERT model in the On the Effectiveness of Compact Biomedical Transformers paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the SciBERT (Base Vocab) model in the SciBERT: A Pretrained Language Model for Scientific Text paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the GoLLIE model in the GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the SciBERT (SciVocab) model in the SciBERT: A Pretrained Language Model for Scientific Text paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BERT Base model in the BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the BERT-CRF model in the Focusing on Potential Named Entities During Active Label Acquisition paper on the NCBI-disease dataset? | F1 |
What metrics were used to measure the Dater model in the Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the PASTA model in the PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-training paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the Binder model in the Binding Language Models in Symbolic Languages paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the ReasTAP-Large model in the ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the TAPEX-Large model in the TAPEX: Table Pre-training via Learning a Neural SQL Executor paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the T5-3b(UnifiedSKG) model in the UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the Salience-aware TAPAS model in the Table-based Fact Verification with Salience-aware Learning paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the TAPAS-Large classifier with Counterfactual + Synthetic pre-training model in the Understanding tables with intermediate pre-training paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the Table-BERT-Horizontal-T+F-Template model in the TabFact: A Large-scale Dataset for Table-based Fact Verification paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the BERT classifier w/o Table model in the TabFact: A Large-scale Dataset for Table-based Fact Verification paper on the TabFact dataset? | Test, Val |
What metrics were used to measure the ConvLSTM (Huber Loss, naive residual path) model in the Temporally Consistent Horizon Lines paper on the KITTI Horizon dataset? | ATV, AUC, MSE |
What metrics were used to measure the V model in the A-Contrario Horizon-First Vanishing Point Detection Using Second-Order Grouping Laws paper on the Eurasian Cities Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the CNN+FULL model in the Detecting Vanishing Points using Global Image Context in a Non-Manhattan World paper on the Eurasian Cities Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the DL-IGP model in the Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection paper on the Eurasian Cities Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the GoogleNet (Huber Loss, horizon line projection) model in the Horizon Lines in the Wild paper on the Eurasian Cities Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the NG-DSAC model in the Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses paper on the Horizon Lines in the Wild dataset? | AUC (horizon error) |
What metrics were used to measure the GoogleNet (Huber Loss, horizon line projection) model in the Horizon Lines in the Wild paper on the Horizon Lines in the Wild dataset? | AUC (horizon error) |
What metrics were used to measure the CNN+FULL model in the Detecting Vanishing Points using Global Image Context in a Non-Manhattan World paper on the Horizon Lines in the Wild dataset? | AUC (horizon error) |
What metrics were used to measure the DL-IGP model in the Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection paper on the Horizon Lines in the Wild dataset? | AUC (horizon error) |
What metrics were used to measure the V model in the A-Contrario Horizon-First Vanishing Point Detection Using Second-Order Grouping Laws paper on the Horizon Lines in the Wild dataset? | AUC (horizon error) |
What metrics were used to measure the V model in the A-Contrario Horizon-First Vanishing Point Detection Using Second-Order Grouping Laws paper on the York Urban Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the CNN+FULL model in the Detecting Vanishing Points using Global Image Context in a Non-Manhattan World paper on the York Urban Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the DL-IGP model in the Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection paper on the York Urban Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the GoogleNet (Huber Loss, horizon line projection) model in the Horizon Lines in the Wild paper on the York Urban Dataset dataset? | AUC (horizon error) |
What metrics were used to measure the Classifier Chain (12-lead) model in the Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain paper on the PhysioNet Challenge 2021 dataset? | PhysioNet Challenge score 2021 |
What metrics were used to measure the Classifier Chain (6-lead) model in the Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain paper on the PhysioNet Challenge 2021 dataset? | PhysioNet Challenge score 2021 |
What metrics were used to measure the Classifier Chain (4-lead) model in the Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain paper on the PhysioNet Challenge 2021 dataset? | PhysioNet Challenge score 2021 |
What metrics were used to measure the Classifier Chain (3-lead) model in the Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain paper on the PhysioNet Challenge 2021 dataset? | PhysioNet Challenge score 2021 |
What metrics were used to measure the Classifier Chain (2-lead) model in the Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain paper on the PhysioNet Challenge 2021 dataset? | PhysioNet Challenge score 2021 |
What metrics were used to measure the V2Sa model in the Voice2Series: Reprogramming Acoustic Models for Time Series Classification paper on the UCR Time Series Classification Archive dataset? | Accuracy (Test) |
What metrics were used to measure the DNN model in the Automatic diagnosis of the 12-lead ECG using a deep neural network paper on the Electrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG) dataset? | F1 (1dAVb), F1 (RBBB), F1 (LBBB), F1 (SB), F1 (AF), F1 (ST) |
What metrics were used to measure the 4th year cardiology resident model in the Automatic diagnosis of the 12-lead ECG using a deep neural network paper on the Electrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG) dataset? | F1 (1dAVb), F1 (RBBB), F1 (LBBB), F1 (SB), F1 (AF), F1 (ST) |
What metrics were used to measure the 5th year medical student model in the Automatic diagnosis of the 12-lead ECG using a deep neural network paper on the Electrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG) dataset? | F1 (1dAVb), F1 (RBBB), F1 (LBBB), F1 (SB), F1 (AF), F1 (ST) |
What metrics were used to measure the 3rd year emergency resident model in the Automatic diagnosis of the 12-lead ECG using a deep neural network paper on the Electrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG) dataset? | F1 (1dAVb), F1 (RBBB), F1 (LBBB), F1 (SB), F1 (AF), F1 (ST) |
What metrics were used to measure the 1D CNN Encoder model in the Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs paper on the PhysioNet Challenge 2020 dataset? | Accuracy(stratified10-fold), F1(stratified10-fold), F2(stratified10-fold), G2(stratified10-fold), PhysioNet/CinC Challenge Score(stratified10-fold), PhysioNet Challenge score (test data), PhysioNet Challenge score 2020 (validation data) |
What metrics were used to measure the 1D CNN Fully Convolutional Network model in the Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs paper on the PhysioNet Challenge 2020 dataset? | Accuracy(stratified10-fold), F1(stratified10-fold), F2(stratified10-fold), G2(stratified10-fold), PhysioNet/CinC Challenge Score(stratified10-fold), PhysioNet Challenge score (test data), PhysioNet Challenge score 2020 (validation data) |
What metrics were used to measure the Yu et. al [[Yu et al.2017a]] model in the Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the vrd-dsr model in the Visual relationship detection with deep structural ranking paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the BLOCK model in the BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the Dai et. al [[Dai, Zhang, and Lin2017]] model in the Detecting Visual Relationships with Deep Relational Networks paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the Liang et. al [[Liang, Lee, and Xing2017]] model in the Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute Detection paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the Peyre et. al [[Peyre et al.2017]] model in the Weakly-supervised learning of visual relations paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the Zhang et. al [[Hanwang Zhang2017]] model in the Visual Translation Embedding Network for Visual Relation Detection paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the Lu et. al [[Lu et al.2016]] model in the Visual Relationship Detection with Language Priors paper on the VRD Relationship Detection dataset? | R@100, R@50 |
What metrics were used to measure the Ours - v model in the Improving Visual Relation Detection using Depth Maps paper on the VRD dataset? | R@50 k=1 |
What metrics were used to measure the Yu et. al [[Yu et al.2017a]] model in the Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation paper on the VRD Phrase Detection dataset? | R@100, R@50 |
What metrics were used to measure the BLOCK model in the BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection paper on the VRD Phrase Detection dataset? | R@100, R@50 |
What metrics were used to measure the Dai et. al [[Dai, Zhang, and Lin2017]] model in the Detecting Visual Relationships with Deep Relational Networks paper on the VRD Phrase Detection dataset? | R@100, R@50 |
What metrics were used to measure the Liang et. al [[Liang, Lee, and Xing2017]] model in the Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute Detection paper on the VRD Phrase Detection dataset? | R@100, R@50 |
What metrics were used to measure the Zhang et. al [[Hanwang Zhang2017]] model in the Visual Translation Embedding Network for Visual Relation Detection paper on the VRD Phrase Detection dataset? | R@100, R@50 |
What metrics were used to measure the Peyre et. al [[Peyre et al.2017]] model in the Weakly-supervised learning of visual relations paper on the VRD Phrase Detection dataset? | R@100, R@50 |
What metrics were used to measure the Lu et. al [[Lu et al.2016]] model in the Visual Relationship Detection with Language Priors paper on the VRD Phrase Detection dataset? | R@100, R@50 |
What metrics were used to measure the Yu et. al [[Yu et al.2017a]] model in the Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation paper on the VRD Predicate Detection dataset? | R@100, R@50 |
What metrics were used to measure the vrd-dsr model in the Visual relationship detection with deep structural ranking paper on the VRD Predicate Detection dataset? | R@100, R@50 |
What metrics were used to measure the BLOCK model in the BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection paper on the VRD Predicate Detection dataset? | R@100, R@50 |
What metrics were used to measure the Dai et. al [[Dai, Zhang, and Lin2017]] model in the Detecting Visual Relationships with Deep Relational Networks paper on the VRD Predicate Detection dataset? | R@100, R@50 |
What metrics were used to measure the Peyre et. al [[Peyre et al.2017]] model in the Weakly-supervised learning of visual relations paper on the VRD Predicate Detection dataset? | R@100, R@50 |
What metrics were used to measure the Lu et. al [[Lu et al.2016]] model in the Visual Relationship Detection with Language Priors paper on the VRD Predicate Detection dataset? | R@100, R@50 |
What metrics were used to measure the Zhang et. al [[Hanwang Zhang2017]] model in the Visual Translation Embedding Network for Visual Relation Detection paper on the VRD Predicate Detection dataset? | R@100, R@50 |
What metrics were used to measure the PEVL model in the PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models paper on the Visual Genome dataset? | R@100, R@50, mR@100, mR@50 |
What metrics were used to measure the BiSLU model in the Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillation paper on the MixATIS dataset? | F1 |
What metrics were used to measure the GL-GIN model in the GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling paper on the MixATIS dataset? | F1 |
What metrics were used to measure the GL-GIN model in the GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling paper on the MixSNIPS dataset? | F1 |
What metrics were used to measure the BiSLU model in the Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillation paper on the MixSNIPS dataset? | F1 |
What metrics were used to measure the TDT 0-6 model in the Efficient Sequence Transduction by Jointly Predicting Tokens and Durations paper on the SLURP dataset? | F1 |
What metrics were used to measure the Partially Fine-tuned HuBERT model in the A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding paper on the SLURP dataset? | F1 |
What metrics were used to measure the Multi-SLURP model in the SLURP: A Spoken Language Understanding Resource Package paper on the SLURP dataset? | F1 |
What metrics were used to measure the Finstreder (Conformer) model in the Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models paper on the SLURP dataset? | F1 |
What metrics were used to measure the Finstreder (Quartznet) model in the Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models paper on the SLURP dataset? | F1 |
What metrics were used to measure the CTRAN model in the CTRAN: CNN-Transformer-based Network for Natural Language Understanding paper on the ATIS dataset? | F1 |
What metrics were used to measure the Bi-model with a decoder model in the A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling paper on the ATIS dataset? | F1 |
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