Automated Historical Fact-Checking by Passage Retrieval, Word Statistics, and Virtual Question-Answering
By Mio Kobayashi, Ai Ishii, Chikara Hoshino, Hiroshi Miyashita, Takuya Matsuzaki. 2017
9 citations recorded by the source corpus.
Subfields: Information Retrieval & Search, Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Retrieval & Search
- Heng Ji
- Dong Yu
- Dan Roth
- Arpit Mittal
- James Thorne
- Andreas Vlachos
- Christos Christodoulopoulos
- Xiaoman Pan
In Natural Language Processing
- Andreas Vlachos
- James Thorne
- Wenpeng Yin
- Dan Roth
- Mohit Bansal
- Sebastian Riedel
- Christos Christodoulopoulos
- Arpit Mittal
Citations in the corpus
- Improving Question Answering with External Knowledge (2019, background): “In this paper, we focus on multiple-choice subject-area QA tasks, where the in-domain reference corpus does not provide sufficient relevant content on its own to answer a significant portion of the questions (Clark et al., 2016; Kobayashi et al., 2017; Welbl et al., 2017; Clark et al., 2018; Mihaylo”
- FEVER: a Large-scale Dataset for Fact Extraction and VERification (2018, background): “In the same vein, Kobayashi et al. (2017) collected a dataset of 412 statements in context from high-school student exams that were validated against Wikipedia and history textbooks.”
- TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification (2018, background): “Kobayashi et al. (2017) release a similar dataset to (Thorne et al., 2018), but they do not consider the evaluation of evidence reasoning.”