prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the Ntumpha model in the Multi-Task Deep Neural Networks for Natural Language Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Densely-Connected Recurrent and Co-Attentive Network Ensemble model in the Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the MFAE model in the What Do Questions Exactly Ask? MFAE: Duplicate Question Identification with Multi-Fusion Asking Emphasis paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Fine-Tuned LM-Pretrained Transformer model in the Improving Language Understanding by Generative Pre-Training paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D DMAN Ensemble model in the Discourse Marker Augmented Network with Reinforcement Learning for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D DMAN Ensemble model in the paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 150D Multiway Attention Network Ensemble model in the Multiway Attention Networks for Modeling Sentence Pairs paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 450D DR-BiLSTM Ensemble model in the DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D CAFE Ensemble model in the Compare, Compress and Propagate: Enhancing Neural Architectures with Alignment Factorization for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the ESIM + ELMo Ensemble model in the Deep contextualized word representations paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the KIM Ensemble model in the Neural Natural Language Inference Models Enhanced with External Knowledge paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the SLRC model in the Explicit Contextual Semantics for Text Comprehension paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the RE2 model in the Simple and Effective Text Matching with Richer Alignment Features paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Densely-Connected Recurrent and Co-Attentive Network model in the Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the DEIM model in the DEIM: An effective deep encoding and interaction model for sentence matching paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 448D Densely Interactive Inference Network (DIIN, code) Ensemble model in the Natural Language Inference over Interaction Space paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D DMAN model in the Discourse Marker Augmented Network with Reinforcement Learning for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D DMAN model in the paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the BiMPM Ensemble model in the Bilateral Multi-Perspective Matching for Natural Language Sentences paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the ESIM + ELMo model in the Deep contextualized word representations paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the KIM model in the Neural Natural Language Inference Models Enhanced with External Knowledge paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D ESIM + 300D Syntactic TreeLSTM model in the Enhanced LSTM for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 450D DR-BiLSTM model in the DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Stochastic Answer Network model in the Stochastic Answer Networks for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D CAFE model in the Compare, Compress and Propagate: Enhancing Neural Architectures with Alignment Factorization for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 150D Multiway Attention Network model in the Multiway Attention Networks for Modeling Sentence Pairs paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Biattentive Classification Network + CoVe + Char model in the Learned in Translation: Contextualized Word Vectors paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the aESIM model in the Attention Boosted Sequential Inference Model paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the CNN-MC [[Kim2014]] model in the Convolutional Neural Networks for Sentence Classification paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 448D Densely Interactive Inference Network (DIIN, code) model in the Natural Language Inference over Interaction Space paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the CT-LSTM [[Tai et al.2015]] model in the Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Enhanced Sequential Inference Model (Chen et al., [2017a]) model in the Enhanced LSTM for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the BiMPM model in the Bilateral Multi-Perspective Matching for Natural Language Sentences paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D re-read LSTM model in the paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D re-read LSTM model in the Reading and Thinking: Re-read LSTM Unit for Textual Entailment Recognition paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 2400D Multiple-Dynamic Self-Attention Model model in the Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence Embedding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D Full tree matching NTI-SLSTM-LSTM w/ global attention model in the Neural Tree Indexers for Text Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D 2-layer Bi-CAS-LSTM model in the Cell-aware Stacked LSTMs for Modeling Sentences paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 200D decomposable attention model with intra-sentence attention model in the A Decomposable Attention Model for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D Dynamic Self-Attention Model model in the Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence Embedding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the DCNN [[Blunsom et al.2014]] model in the A Convolutional Neural Network for Modelling Sentences paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the CBS-1 + ESIM model in the Parameter Re-Initialization through Cyclical Batch Size Schedules paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 512D Dynamic Meta-Embeddings model in the Dynamic Meta-Embeddings for Improved Sentence Representations paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D BiLSTM with generalized pooling model in the Enhancing Sentence Embedding with Generalized Pooling paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D Hierarchical BiLSTM with Max Pooling (HBMP, code) model in the Sentence Embeddings in NLI with Iterative Refinement Encoders paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Densely-Connected Recurrent and Co-Attentive Network (encoder) model in the Semantic Sentence Matching with Densely-connected Recurrent and Co-attentive Information paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D Reinforced Self-Attention Network model in the Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Distance-based Self-Attention Network model in the Distance-based Self-Attention Network for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 200D decomposable attention model model in the A Decomposable Attention Model for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 450D LSTMN with deep attention fusion model in the Long Short-Term Memory-Networks for Machine Reading paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 2-layer LSTM [[Tai et al.2015]] model in the Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D mLSTM word-by-word attention model model in the Learning Natural Language Inference with LSTM paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D Gumbel TreeLSTM encoders model in the Learning to Compose Task-Specific Tree Structures paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D Residual stacked encoders model in the Shortcut-Stacked Sentence Encoders for Multi-Domain Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Star-Transformer (no cross sentence attention) model in the Star-Transformer paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D CAFE (no cross-sentence attention) model in the Compare, Compress and Propagate: Enhancing Neural Architectures with Alignment Factorization for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 1200D REGMAPR (Base+Reg) model in the paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D Residual stacked encoders model in the Shortcut-Stacked Sentence Encoders for Multi-Domain Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D LSTMN with deep attention fusion model in the Long Short-Term Memory-Networks for Machine Reading paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D Gumbel TreeLSTM encoders model in the Learning to Compose Task-Specific Tree Structures paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D Directional self-attention network encoders model in the DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D (300+300) Deep Gated Attn. BiLSTM encoders model in the Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D MMA-NSE encoders with attention model in the Neural Semantic Encoders paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 50D stacked TC-LSTMs model in the Modelling Interaction of Sentence Pair with coupled-LSTMs paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D (300+300) BiLSTM encoders with intra-attention and symbolic preproc. model in the Learning Natural Language Inference using Bidirectional LSTM model and Inner-Attention paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the LSTM [[Tai et al.2015]] model in the Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Stacked Bi-LSTMs (shortcut connections, max-pooling) model in the Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D NSE encoders model in the Neural Semantic Encoders paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 100D DF-LSTM model in the Deep Fusion LSTMs for Text Semantic Matching paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 4096D BiLSTM with max-pooling model in the Supervised Learning of Universal Sentence Representations from Natural Language Inference Data paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Bi-LSTM sentence encoder (max-pooling) model in the Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Stacked Bi-LSTMs (shortcut connections, max-pooling, attention) model in the Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D (300+300) BiLSTM encoders with intra-attention model in the Learning Natural Language Inference using Bidirectional LSTM model and Inner-Attention paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the SWEM-max model in the Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 100D LSTMs w/ word-by-word attention model in the Reasoning about Entailment with Neural Attention paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D NTI-SLSTM-LSTM encoders model in the Neural Tree Indexers for Text Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 600D (300+300) BiLSTM encoders model in the Learning Natural Language Inference using Bidirectional LSTM model and Inner-Attention paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D SPINN-PI encoders model in the A Fast Unified Model for Parsing and Sentence Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D Tree-based CNN encoders model in the Natural Language Inference by Tree-Based Convolution and Heuristic Matching paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 1024D GRU encoders w/ unsupervised 'skip-thoughts' pre-training model in the Order-Embeddings of Images and Language paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the DELTA (LSTM) model in the DELTA: A DEep learning based Language Technology plAtform paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 300D LSTM encoders model in the A Fast Unified Model for Parsing and Sentence Understanding paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the + Unigram and bigram features model in the A large annotated corpus for learning natural language inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the 100D LSTM encoders model in the A large annotated corpus for learning natural language inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Unlexicalized features model in the A large annotated corpus for learning natural language inference paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the MT-DNN-SMART_100%ofTrainingData model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the MT-DNN-SMART_10%ofTrainingData model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the MT-DNN-SMART_1%ofTrainingData model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the MT-DNN-SMART_0.1%ofTrainingData model in the SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the SplitEE-S model in the SplitEE: Early Exit in Deep Neural Networks with Split Computing paper on the SNLI dataset? | % Test Accuracy, % Train Accuracy, Parameters, Dev Accuracy, % Dev Accuracy, Accuracy |
What metrics were used to measure the Human Benchmark model in the RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the ruRoberta-large finetune model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the ruT5-large-finetune model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the ruT5-base-finetune model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the ruBert-large finetune model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the RuGPT3Large model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the ruBert-base finetune model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the SBERT_Large_mt_ru_finetuning model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the SBERT_Large model in the paper on the LiDiRus dataset? | MCC |
What metrics were used to measure the RuBERT plain model in the paper on the LiDiRus dataset? | MCC |
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