Standford Question Answering Dataset (SQuAD) is a reading comprehension dataset by Standford University and has two versions. 斯坦福问答数据集是由斯坦福大学创建的阅读理解数据集,有两个版本。 数据列表 数据名称上传日期大小下载 Know What You Don’t Know- Unanswerable Questions for SQuAD paper.pdf2020-11...
Question Answering on SQuAD This project implements models that train on theStanford Question Answering Dataset(SQuAD). The SQuAD dataset is comprised of pairs of passages and questions given in English text where the answer to the question is a span of text in the passage. The goal of a mode...
Systematic Error Analysis of the Stanford Question Answering Datasetdoi:10.18653/V1/W18-2602Marc-Antoine RondeauTimothy J. HazenAssociation for Computational LinguisticsMeeting of the Association for Computational Linguistics
manually annotated datasets. The Stanford Question Answering Dataset (SQuAD) is the most widely used benchmark dataset for machine reading comprehension research. Stanford released SQuAD in July 2016 and it consists of 100,000 human-labeled question and answer pairs. The passages in...
SQuAD: the Standford Question Answering Dataset (SQuAD) is a selection of questions based on a collection of articles obtained from the English Wikipedia57. It was created due to the need for a large and high-quality dataset. In this study, the first version (v1.1) is used, as every ques...
TheStanford Question Answering Datasetis an active project for evaluating the question answering task using a hidden test set. To scrape the current content run: python -m scrapers.squad Licence: CC-BY-SA-4 RedditSota TheRedditSota repositorylists the best method for a variety of tasks across ...
Other fields of applied ML have seen rapid advancement in recent years in large part due to the creation and use of standardized community benchmarks such as ImageNet7 (20,000+ citations) for image classification and the Stanford Question Answering Dataset8 (1400+ citations) for NLP. While ...
(BERT) have been dominating the leaderboard when tested on the Stanford Question Answering Dataset (SQuAD) 2.0, differentiated from SQuAD 1.0 due to a ... M Reed 被引量: 0发表: 2022年 Comparing Approaches to Question-Answering on SQuAD 2.0 In this project, we qualitatively and quantitatively ...
For example, to train a Multitask Question Answering Network (MQAN) on the Stanford Question Answering Dataset (SQuAD) on GPU 0: nvidia-docker run -it --rm -v`pwd`:/decaNLP/ -u$(id -u):$(id -g)bmccann/decanlp:cuda9_torch041 bash -c"python /decaNLP/train.py --train_tasks squad...
Synthetic question-answering dataset to formally analyze the chain-of-thought output of large language models on a reasoning task. - asaparov/prontoqa