prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
|---|---|
What metrics were used to measure the Separate And Diffuse model in the Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation paper on the WSJ0-3mix dataset? | SI-SDRi |
What metrics were used to measure the MossFormer (M) + DM model in the MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions paper on the WSJ0-3mix dataset? | SI-SDRi |
What metrics were used to measure the SepIt model in the SepIt: Approaching a Single Channel Speech Separation Bound paper on the WSJ0-3mix dataset? | SI-SDRi |
What metrics were used to measure the SepFormer model in the Attention is All You Need in Speech Separation paper on the WSJ0-3mix dataset? | SI-SDRi |
What metrics were used to measure the Sandglasset model in the Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation paper on the WSJ0-3mix dataset? | SI-SDRi |
What metrics were used to measure the Gated DualPathRNN model in the Voice Separation with an Unknown Number of Multiple Speakers paper on the WSJ0-3mix dataset? | SI-SDRi |
What metrics were used to measure the U-Net model in the Singing Voice Separation with Deep U-Net Convolutional Networks paper on the iKala dataset? | NSDR |
What metrics were used to measure the Separate And Diffuse model in the Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation paper on the Libri10Mix dataset? | SI-SDRi |
What metrics were used to measure the SepIt model in the SepIt: Approaching a Single Channel Speech Separation Bound paper on the Libri10Mix dataset? | SI-SDRi |
What metrics were used to measure the Hungarian PIT model in the Many-Speakers Single Channel Speech Separation with Optimal Permutation Training paper on the Libri10Mix dataset? | SI-SDRi |
What metrics were used to measure the ConvNet model in the Event2Mind: Commonsense Inference on Events, Intents, and Reactions paper on the Event2Mind dev dataset? | Average Cross-Ent |
What metrics were used to measure the BiRNN 100d model in the Event2Mind: Commonsense Inference on Events, Intents, and Reactions paper on the Event2Mind dev dataset? | Average Cross-Ent |
What metrics were used to measure the ViLT model in the WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models paper on the WinoGAViL dataset? | Jaccard Index |
What metrics were used to measure the PaLM 2 (few-shot, k=3, Direct) model in the PaLM 2 Technical Report paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the PaLM 540B (few-shot, k=3) model in the BloombergGPT: A Large Language Model for Finance paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the PaLM 2 (few-shot, k=3, CoT) model in the PaLM 2 Technical Report paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the Chinchilla-70B (few-shot, k=5) model in the Training Compute-Optimal Large Language Models paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the GPT-NeoX (few-shot, k=3) model in the BloombergGPT: A Large Language Model for Finance paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the BLOOM 176B (few-shot, k=3) model in the BloombergGPT: A Large Language Model for Finance paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the OPT 66B (few-shot, k=3) model in the BloombergGPT: A Large Language Model for Finance paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the Gopher-280B (few-shot, k=5) model in the Scaling Language Models: Methods, Analysis & Insights from Training Gopher paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the BloombergGPT (few-shot, k=3) model in the BloombergGPT: A Large Language Model for Finance paper on the BIG-bench (Causal Judgment) dataset? | Accuracy |
What metrics were used to measure the GPT-4 (few-shot, k=25) model in the GPT-4 Technical Report paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 2 (few-shot, CoT, SC) model in the PaLM 2 Technical Report paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 540B (Self Improvement, Self Consistency) model in the Large Language Models Can Self-Improve paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 540B (Self Consistency) model in the Large Language Models Can Self-Improve paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 540B (Self Improvement, CoT Prompting) model in the Large Language Models Can Self-Improve paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 540B (Self Improvement, Standard-Prompting) model in the Large Language Models Can Self-Improve paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 540B (Standard-Prompting) model in the Large Language Models Can Self-Improve paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the ST-MoE-32B model in the ST-MoE: Designing Stable and Transferable Sparse Expert Models paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GPT-3.5 (few-shot, k=25) model in the GPT-4 Technical Report paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 540B (CoT Prompting) model in the Large Language Models Can Self-Improve paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 2-L (one-shot) model in the PaLM 2 Technical Report paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GAL 120B (zero-shot) model in the Galactica: A Large Language Model for Science paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 2-M (one-shot) model in the PaLM 2 Technical Report paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the PaLM 2-S (one-shot) model in the PaLM 2 Technical Report paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the LLaMA 33B (zero-shot) model in the LLaMA: Open and Efficient Foundation Language Models paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the LLaMA 65B (zero-shot) model in the LLaMA: Open and Efficient Foundation Language Models paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GPT-3 175B (1 shot) model in the Language Models are Few-Shot Learners paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the LLaMA 13B (zero-shot) model in the LLaMA: Open and Efficient Foundation Language Models paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GPT-3 175B (0 shot) model in the Language Models are Few-Shot Learners paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GPT-3 (zero-shot) model in the Galactica: A Large Language Model for Science paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the BLOOM 176B (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GLaM 64B/64E (0 shot) model in the GLaM: Efficient Scaling of Language Models with Mixture-of-Experts paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the Bloomberg GPT (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GLaM 64B/64E (1 shot) model in the GLaM: Efficient Scaling of Language Models with Mixture-of-Experts paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the LLaMA 7B (zero-shot) model in the LLaMA: Open and Efficient Foundation Language Models paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the GPT-NeoX (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the phi-1.5-web 1.3B (zero-shot) model in the Textbooks Are All You Need II: phi-1.5 technical report paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the OPT 66B (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the OPT-175B model in the SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the SparseGPT (175B, 50% Sparsity) model in the SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the SparseGPT (175B, 4:8 Sparsity) model in the SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the SparseGPT (175B, 2:4 Sparsity) model in the SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the BLOOM (few-shot, k=5) model in the Galactica: A Large Language Model for Science paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the OPT (few-shot, k=5) model in the Galactica: A Large Language Model for Science paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the OPT-175B (50% Sparsity) model in the SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot paper on the ARC (Challenge) dataset? | Accuracy |
What metrics were used to measure the DeBERTa-1.5B model in the DeBERTa: Decoding-enhanced BERT with Disentangled Attention paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the PaLM 540B (finetuned) model in the PaLM: Scaling Language Modeling with Pathways paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the T5-11B model in the Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the GESA model in the Integrating a Heterogeneous Graph with Entity-aware Self-attention using Relative Position Labels for Reading Comprehension Model paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the LUKE-Graph model in the LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehension paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the LUKE (single model) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the KELM (finetuning RoBERTa-large based single model) model in the KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational Graphs paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the XLNet + MTL + Verifier (ensemble) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the CSRLM (single model) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the XLNet + MTL + Verifier (single model) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the {SKG-NET} (single model) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the KELM (finetuning BERT-large based single model) model in the KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational Graphs paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the SKG-BERT (single model) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the KT-NET (single model) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the DCReader+BERT (single model) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the GraphBert (single) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the GraphBert-WordNet (single) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the GraphBert-NELL (single) model in the paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the BERT-Base (single model) model in the BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the N-Grammer model in the N-Grammer: Augmenting Transformers with latent n-grams paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the PaLM 2-L (one-shot) model in the PaLM 2 Technical Report paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the PaLM 2-M (one-shot) model in the PaLM 2 Technical Report paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the PaLM 2-S (one-shot) model in the PaLM 2 Technical Report paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the GPT 3 (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the AlexaTM 20B model in the AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the Bloomberg GPT (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the OPT 66B (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the BLOOM 176B (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the FLAN 137B zero-shot model in the Finetuned Language Models Are Zero-Shot Learners paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the GPT-NeoX (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the ReCoRD dataset? | EM, F1 |
What metrics were used to measure the DeBERTaV3-large+KEAR model in the Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the PaLM 2 (few‑shot, CoT, SC) model in the PaLM 2 Technical Report paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the KEAR model in the Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the DEKCOR model in the Fusing Context Into Knowledge Graph for Commonsense Question Answering paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the MUPPET Roberta Large model in the Muppet: Massive Multi-task Representations with Pre-Finetuning paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the UnifiedQA* Khashabi et al. (2020) model in the UnifiedQA: Crossing Format Boundaries With a Single QA System paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the DRAGON model in the Deep Bidirectional Language-Knowledge Graph Pretraining paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the Albert Lan et al. (2020) (ensemble) model in the ALBERT: A Lite BERT for Self-supervised Learning of Language Representations paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the QA-GNN model in the QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the XLNet+GraphReason model in the Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the GrapeQA: PEGA model in the GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answering paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the RoBERTa+HyKAS Ma et al. (2019) model in the Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering paper on the CommonsenseQA dataset? | Accuracy |
What metrics were used to measure the GPT-3 Direct Finetuned model in the Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention paper on the CommonsenseQA dataset? | Accuracy |
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