[PDF] arxiv.org

KBQA: learning question answering over QA corpora and knowledge bases

W Cui, Y Xiao, H Wang, Y Song, S Hwang… - arXiv preprint arXiv …, 2019 - arxiv.org
Question answering (QA) has become a popular way for humans to access billion-scale
knowledge bases. Unlike web search, QA over a knowledge base gives out accurate and …
被引用次数：294 相关文章 所有 9 个版本
[PDF] arxiv.org

UNIQORN: unified question answering over RDF knowledge graphs and natural language text

S Pramanik, J Alabi, RS Roy, G Weikum - arXiv preprint arXiv:2108.08614, 2021 - arxiv.org
Question answering over RDF data like knowledge graphs has been greatly advanced, with
a number of good systems providing crisp answers for natural language questions or …
被引用次数：34 相关文章 所有 4 个版本
[PDF] arxiv.org

Decaf: Joint decoding of answers and logical forms for question answering over knowledge bases

D Yu, S Zhang, P Ng, H Zhu, AH Li, J Wang… - arXiv preprint arXiv …, 2022 - arxiv.org
Question answering over knowledge bases (KBs) aims to answer natural language
questions with factual information such as entities and relations in KBs. Previous methods …
被引用次数：41 相关文章 所有 6 个版本
[PDF] arxiv.org

Improving question answering with external knowledge

X Pan, K Sun, D Yu, J Chen, H Ji, C Cardie… - arXiv preprint arXiv …, 2019 - arxiv.org
We focus on multiple-choice question answering (QA) tasks in subject areas such as
science, where we require both broad background knowledge and the facts from the given …
被引用次数：70 相关文章 所有 11 个版本
[PDF] arxiv.org

Question answering on knowledge bases and text using universal schema and memory networks

R Das, M Zaheer, S Reddy, A McCallum - arXiv preprint arXiv:1704.08384, 2017 - arxiv.org
Existing question answering methods infer answers either from a knowledge base or from
raw text. While knowledge base (KB) methods are good at answering compositional …
被引用次数：162 相关文章 所有 13 个版本
[PDF] arxiv.org

Grape: Knowledge graph enhanced passage reader for open-domain question answering

M Ju, W Yu, T Zhao, C Zhang, Y Ye - arXiv preprint arXiv:2210.02933, 2022 - arxiv.org
A common thread of open-domain question answering (QA) models employs a retriever-
reader pipeline that first retrieves a handful of relevant passages from Wikipedia and then …
被引用次数：28 相关文章 所有 7 个版本
[PDF] arxiv.org

Unik-qa: Unified representations of structured and unstructured knowledge for open-domain question answering

B Oguz, X Chen, V Karpukhin, S Peshterliev… - arXiv preprint arXiv …, 2020 - arxiv.org
We study open-domain question answering with structured, unstructured and semi-
structured knowledge sources, including text, tables, lists and knowledge bases. Departing …
被引用次数：94 相关文章 所有 5 个版本
[PDF] arxiv.org

R2-D2: A modular baseline for open-domain question answering

M Fajcik, M Docekal, K Ondrej, P Smrz - arXiv preprint arXiv:2109.03502, 2021 - arxiv.org
This work presents a novel four-stage open-domain QA pipeline R2-D2 (Rank twice, reaD
twice). The pipeline is composed of a retriever, passage reranker, extractive reader …
被引用次数：41 相关文章 所有 5 个版本
[PDF] arxiv.org

Simple and effective semi-supervised question answering

B Dhingra, D Pruthi, D Rajagopal - arXiv preprint arXiv:1804.00720, 2018 - arxiv.org
Recent success of deep learning models for the task of extractive Question Answering (QA)
is hinged on the availability of large annotated corpora. However, large domain specific …
被引用次数：82 相关文章 所有 5 个版本
[PDF] arxiv.org

KQA pro: A dataset with explicit compositional programs for complex question answering over knowledge base

S Cao, J Shi, L Pan, L Nie, Y Xiang, L Hou, J Li… - arXiv preprint arXiv …, 2020 - arxiv.org
Complex question answering over knowledge base (Complex KBQA) is challenging
because it requires various compositional reasoning capabilities, such as multi-hop …
被引用次数：88 相关文章 所有 6 个版本