paper-with-me

홈 › Papers

Multi Document Reading Comprehension

2022-01-05 · Avi Chawla

Reading Comprehension (RC) is a task of answering a question from a given passage or a set of passages. In the case of multiple passages, the task is to find the best possible answer to the question. Recent trials and experiments in the field of Natural Language Processing (NLP) have proved that machines can be provided with the ability to not only process the text in the passage and understand its meaning to answer the question from the passage, but also can surpass the Human Performance on many datasets such as Standford's Question Answering Dataset (SQuAD). This paper presents a study on Reading Comprehension and its evolution in Natural Language Processing over the past few decades. We shall also study how the task of Single Document Reading Comprehension acts as a building block for our Multi-Document Reading Comprehension System. In the latter half of the paper, we'll be studying about a recently proposed model for Multi-Document Reading Comprehension - RE3QA that is comprised of a Reader, Retriever, and a Re-ranker based network to fetch the best possible answer from a given set of passages.

📄 PDF Abstract BibTeX arXiv:2201.01706

Code (0)

등록된 구현이 없습니다.

Tasks

Question AnsweringReading Comprehension

Similar Papers 제목 키워드 기반

Weighted Global Normalization for Multiple Choice Reading Comprehension over Long Documents

2018-12-05 · Aditi Chaudhary, Bhargavi Paranjape, Michiel de Jong

Motivated by recent evidence pointing out the fragility of high-performing span prediction models, we direct our attention to multiple choice reading comprehension. In particular, this work introduces a novel method for …

Answer SelectionMultiple-choicePredictionReading Comprehension

RoR: Read-over-Read for Long Document Machine Reading Comprehension

2021-09-10 · Findings (EMNLP) 2021 11 · Jing Zhao, Junwei Bao, Yifan Wang, Yongwei Zhou 외

Transformer-based pre-trained models, such as BERT, have achieved remarkable results on machine reading comprehension. However, due to the constraint of encoding length (e.g., 512 WordPiece tokens), a long document is us…

Machine Reading ComprehensionReading ComprehensionTriviaQA

CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension

2019-12-19 · Xingyi Duan, Baoxin Wang, Ziyue Wang, Wentao Ma 외

We present a Chinese judicial reading comprehension (CJRC) dataset which contains approximately 10K documents and almost 50K questions with answers. The documents come from judgment documents and the questions are annota…

DiversityMachine Reading ComprehensionReading Comprehension

Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network

2020-06-11 · Zeyun Tang, Yongliang Shen, Xinyin Ma, Wei Xu 외

Multi-hop reading comprehension across multiple documents attracts much attention recently. In this paper, we propose a novel approach to tackle this multi-hop reading comprehension problem. Inspired by human reasoning p…

Multi-Hop Reading ComprehensionReading Comprehension

Deep Understanding based Multi-Document Machine Reading Comprehension

2022-02-25 · Feiliang Ren, Yongkang Liu, Bochao Li, Zhibo Wang 외

Most existing multi-document machine reading comprehension models mainly focus on understanding the interactions between the input question and documents, but ignore following two kinds of understandings. First, to under…

Machine Reading ComprehensionReading ComprehensionTriviaQA