prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
|---|---|
What metrics were used to measure the TubeDETR model in the TubeDETR: Spatio-Temporal Video Grounding with Transformers paper on the VidSTG dataset? | Declarative m_vIoU, Declarative vIoU@0.3, Declarative vIoU@0.5, Interrogative m_vIoU, Interrogative vIoU@0.3, Interrogative vIoU@0.5 |
What metrics were used to measure the CZ-Det model in the Cascaded Zoom-in Detector for High Resolution Aerial Images paper on the VisDrone dataset? | AP50 |
What metrics were used to measure the TransMind model in the Open-TransMind: A New Baseline and Benchmark for 1st Foundation Model Challenge of Intelligent Transportation paper on the CeyMo dataset? | mAP |
What metrics were used to measure the YOLOv7 model in the YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors paper on the CeyMo dataset? | mAP |
What metrics were used to measure the TOOD model in the TOOD: Task-aligned One-stage Object Detection paper on the CeyMo dataset? | mAP |
What metrics were used to measure the YOLOX model in the YOLOX: Exceeding YOLO Series in 2021 paper on the CeyMo dataset? | mAP |
What metrics were used to measure the Sparse R-CNN model in the Sparse R-CNN: End-to-End Object Detection with Learnable Proposals paper on the CeyMo dataset? | mAP |
What metrics were used to measure the InternImage-H model in the InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions paper on the BDD100K val dataset? | mAP |
What metrics were used to measure the PP-YOLOE model in the PP-YOLOE: An evolved version of YOLO paper on the BDD100K val dataset? | mAP |
What metrics were used to measure the HRFuser-T model in the HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection paper on the Dense Fog dataset? | dense fog hard (AP), light fog hard (AP), snow/rain hard (AP) |
What metrics were used to measure the Deep Entropy Fusion model in the Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather paper on the Dense Fog dataset? | dense fog hard (AP), light fog hard (AP), snow/rain hard (AP) |
What metrics were used to measure the HRFuser-T model in the HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection paper on the Clear Weather dataset? | clear hard (AP) |
What metrics were used to measure the Deep Entropy Fusion model in the Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather paper on the Clear Weather dataset? | clear hard (AP) |
What metrics were used to measure the Yolov8x (640x640) model in the FishEye8K: A Benchmark and Dataset for Fisheye Camera Object Detection paper on the FishEye8K dataset? | mAP |
What metrics were used to measure the rotated-retinanet-rbox-r360_r50_fpn_6x.py model in the TRR360D: A dataset for 360 degree rotated rectangular box table detection paper on the TRR360D dataset? | AP50(T<90), AP90(T<90) |
What metrics were used to measure the GLIP model in the Grounded Language-Image Pre-training paper on the RF100 dataset? | Average mAP |
What metrics were used to measure the MAET model in the Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection paper on the ExDark dataset? | mAP |
What metrics were used to measure the TempoRadar model in the Exploiting Temporal Relations on Radar Perception for Autonomous Driving paper on the RADIATE dataset? | mAP@0.3 |
What metrics were used to measure the GPT-4 (few-shot, k=10) model in the GPT-4 Technical Report paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the TheBloke/llama-2-70b-Guanaco-QLoRA-fp16 (10-shot) model in the QLoRA: Efficient Finetuning of Quantized LLMs paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the PaLM 2-L (one-shot) model in the PaLM 2 Technical Report paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the PaLM 2-M (one-shot) model in the PaLM 2 Technical Report paper on the HellaSwag 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 HellaSwag dataset? | Accuracy |
What metrics were used to measure the LLaMA-65B+CFG (zero-shot) model in the Stay on topic with Classifier-Free Guidance paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the PaLM 2-S (one-shot) model in the PaLM 2 Technical Report paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the GPT-3.5 (few-shot, k=10) model in the GPT-4 Technical Report paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the LLaMA-30B+CFG (zero-shot) model in the Stay on topic with Classifier-Free Guidance paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the LLaMA 2 70B (zero-shot) model in the Llama 2: Open Foundation and Fine-Tuned Chat Models paper on the HellaSwag 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 HellaSwag dataset? | Accuracy |
What metrics were used to measure the PaLM-540B (Few-Shot) model in the PaLM: Scaling Language Modeling with Pathways paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the PaLM-540B (One-Shot) model in the PaLM: Scaling Language Modeling with Pathways paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the PaLM-540B (Zero-Shot) model in the PaLM: Scaling Language Modeling with Pathways paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the LLaMA 2 34B (zero-shot) model in the Llama 2: Open Foundation and Fine-Tuned Chat Models paper on the HellaSwag 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 HellaSwag dataset? | Accuracy |
What metrics were used to measure the Megatron-Turing NLG 530B (Few-Shot) model in the Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the LLaMA-13B+CFG (zero-shot) model in the Stay on topic with Classifier-Free Guidance paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the Chinchilla (Zero-Shot) model in the Training Compute-Optimal Large Language Models paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the LLaMA 2 13B (zero-shot) model in the Llama 2: Open Foundation and Fine-Tuned Chat Models paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the Megatron-Turing NLG 530B (One-Shot) model in the Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the GPT-3 175B (Few-Shot) model in the Language Models are Few-Shot Learners paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the Gopher (zero-shot) model in the Scaling Language Models: Methods, Analysis & Insights from Training Gopher paper on the HellaSwag 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 HellaSwag dataset? | Accuracy |
What metrics were used to measure the GPT-3 (zero-shot) model in the Language Models are Few-Shot Learners paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the LLaMA 2 7B (zero-shot) model in the Llama 2: Open Foundation and Fine-Tuned Chat Models paper on the HellaSwag 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 HellaSwag dataset? | Accuracy |
What metrics were used to measure the Blooomberg GPT (one-shot) model in the BloombergGPT: A Large Language Model for Finance paper on the HellaSwag 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 HellaSwag 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 HellaSwag dataset? | Accuracy |
What metrics were used to measure the Sheared-LLaMA-2.7B (50B) model in the Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning paper on the HellaSwag 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 HellaSwag dataset? | Accuracy |
What metrics were used to measure the Open-LLaMA-3B-v2 model in the Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the Sheared-LLaMA-1.3B (50B) model in the Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the FLAN 137B (zero-shot) model in the Finetuned Language Models Are Zero-Shot Learners paper on the HellaSwag dataset? | Accuracy |
What metrics were used to measure the PJ-X model in the CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations paper on the CLEVR-X dataset? | B4, M, RL, C, Acc |
What metrics were used to measure the FM model in the CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations paper on the CLEVR-X dataset? | B4, M, RL, C, Acc |
What metrics were used to measure the OFA-X model in the Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations paper on the VQA-X dataset? | Human Explanation Rating |
What metrics were used to measure the OFA-X-MT model in the Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations paper on the VQA-X dataset? | Human Explanation Rating |
What metrics were used to measure the OFA-X-MT model in the Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations paper on the VCR dataset? | Human Explanation Rating |
What metrics were used to measure the OFA-X model in the Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations paper on the VCR dataset? | Human Explanation Rating |
What metrics were used to measure the Ground-truth Caption -> GPT3 (Oracle) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Human (%) |
What metrics were used to measure the Predicted Caption -> GPT3 model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Human (%) |
What metrics were used to measure the BLIP2 FlanT5-XXL (Fine-tuned) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Human (%) |
What metrics were used to measure the BLIP2 FlanT5-XL (Fine-tuned) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Human (%) |
What metrics were used to measure the BLIP2 FlanT5-XXL (Zero-shot) model in the Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images paper on the WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images dataset? | Human (%) |
What metrics were used to measure the OFA-X model in the Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations paper on the e-SNLI-VE dataset? | Human Explanation Rating |
What metrics were used to measure the OFA-X-MT model in the Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations paper on the e-SNLI-VE dataset? | Human Explanation Rating |
What metrics were used to measure the APOLLO model in the APOLLO: An Optimized Training Approach for Long-form Numerical Reasoning paper on the ConvFinQA dataset? | Execution Accuracy, Program Accuracy |
What metrics were used to measure the FinQANet (RoBERTa-large) model in the ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering paper on the ConvFinQA dataset? | Execution Accuracy, Program Accuracy |
What metrics were used to measure the T5 model in the The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics paper on the SGD dataset? | METEOR |
What metrics were used to measure the BART model in the The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics paper on the SGD dataset? | METEOR |
What metrics were used to measure the DF-Net model in the Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog paper on the Kvret dataset? | Entity F1 |
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 KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the COMET model in the Contextualize Knowledge Bases with Transformer for End-to-end Task-Oriented Dialogue Systems paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the DF-Net model in the Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the GLMP model in the Global-to-local Memory Pointer Networks for Task-Oriented Dialogue paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the TTOS model in the Amalgamating Knowledge from Two Teachers for Task-oriented Dialogue System with Adversarial Training paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the KB-retriever model in the Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the DSR model in the Sequence-to-Sequence Learning for Task-oriented Dialogue with Dialogue State Representation paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the KV Retrieval Net model in the Key-Value Retrieval Networks for Task-Oriented Dialogue paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the THPN model in the A Template-guided Hybrid Pointer Network for Knowledge-based Task-oriented Dialogue Systems paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the Mem2Seq model in the Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems paper on the KVRET dataset? | Entity F1, BLEU |
What metrics were used to measure the BART (TextBox 2.0) model in the TextBox 2.0: A Text Generation Library with Pre-trained Language Models paper on the MULTIWOZ 2.0 dataset? | BLEU-4, Score |
What metrics were used to measure the ACE model in the Automated Concatenation of Embeddings for Structured Prediction paper on the SemEval-2016 Task 5 Subtask 1 (Dutch) dataset? | F1 |
What metrics were used to measure the M-BERT+Flair+Word+Char model in the Structure-Level Knowledge Distillation For Multilingual Sequence Labeling paper on the SemEval-2016 Task 5 Subtask 1 (Dutch) dataset? | F1 |
What metrics were used to measure the ACE model in the Automated Concatenation of Embeddings for Structured Prediction paper on the SemEval-2016 Task 5 Subtask 1 (Russian) dataset? | F1 |
What metrics were used to measure the M-BERT+Word+Char model in the Structure-Level Knowledge Distillation For Multilingual Sequence Labeling paper on the SemEval-2016 Task 5 Subtask 1 (Russian) dataset? | F1 |
What metrics were used to measure the RACL - Laptops model in the YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews paper on the YASO - YELP dataset? | F1 |
What metrics were used to measure the DE-CNN model in the Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction paper on the SemEval 2016 Task 5 Sub Task 1 Slot 2 dataset? | Restaurant (F1) |
What metrics were used to measure the ACE model in the Automated Concatenation of Embeddings for Structured Prediction paper on the SemEval-2016 Task 5 Subtask 1 dataset? | F1 |
What metrics were used to measure the Wei et al. (2020) model in the Don't Eclipse Your Arts Due to Small Discrepancies: Boundary Repositioning with a Pointer Network for Aspect Extraction paper on the SemEval-2016 Task 5 Subtask 1 dataset? | F1 |
What metrics were used to measure the M-BERT+Flair+Word+Char model in the Structure-Level Knowledge Distillation For Multilingual Sequence Labeling paper on the SemEval-2016 Task 5 Subtask 1 dataset? | F1 |
What metrics were used to measure the ACE model in the Automated Concatenation of Embeddings for Structured Prediction paper on the SemEval-2016 Task 5 Subtask 1 (Spanish) dataset? | F1 |
What metrics were used to measure the M-BERT+Flair+Word+Char model in the Structure-Level Knowledge Distillation For Multilingual Sequence Labeling paper on the SemEval-2016 Task 5 Subtask 1 (Spanish) dataset? | F1 |
What metrics were used to measure the DE-CNN model in the Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction paper on the SemEval 2015 Task 12 dataset? | Restaurant (F1) |
What metrics were used to measure the InstructABSA model in the InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis paper on the SemEval 2014 Task 4 Sub Task 1 dataset? | Laptop (F1) |
What metrics were used to measure the DE-CNN model in the Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction paper on the SemEval 2014 Task 4 Sub Task 1 dataset? | Laptop (F1) |
What metrics were used to measure the InstructABSA model in the InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis paper on the SemEval 2014 Task 4 Sub Task 2 dataset? | Laptop (F1), Restaurant (F1), Mean F1 (Laptop + Restaurant) |
What metrics were used to measure the ACE model in the Automated Concatenation of Embeddings for Structured Prediction paper on the SemEval 2014 Task 4 Sub Task 2 dataset? | Laptop (F1), Restaurant (F1), Mean F1 (Laptop + Restaurant) |
What metrics were used to measure the PH-SUM model in the Improving BERT Performance for Aspect-Based Sentiment Analysis paper on the SemEval 2014 Task 4 Sub Task 2 dataset? | Laptop (F1), Restaurant (F1), Mean F1 (Laptop + Restaurant) |
What metrics were used to measure the BAT model in the Adversarial Training for Aspect-Based Sentiment Analysis with BERT paper on the SemEval 2014 Task 4 Sub Task 2 dataset? | Laptop (F1), Restaurant (F1), Mean F1 (Laptop + Restaurant) |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.