Edit 2019/Cure My FEVER : Building, Breaking and Fixing Models for Fact-Checking: 2024/Main Page

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This submission has been accepted for WikiConference North America 2019.



Title:

Main Page

Theme:

Reliability of Information
+ Tech & Tools

Type of session:

Presentation

Abstract:

Many tasks such as question answering and reading comprehension rely on information extracted from unreliable sources. These systems would thus benefit from knowing whether a statement from an unreliable source is correct. We present experiments on the Fact Extraction and VERification (FEVER) dataset, which involves selecting sentences from Wikipedia and predicting whether a claim is supported by those sentences, refuted, or there is not enough information. We describe results across three phases: the development of a fact-checking system, the creation of adversarial examples, and the improvement of the system in handling adversarial examples.

Academic Peer Review option:

No

Author name:

Tariq Alhindi

E-mail address:

tariq@cs.columbia.edu

Wikimedia username:

Affiliated organization(s):

Columbia University

Estimated time:

30 min

Preferred room size:

Special requests:

Have you presented on this topic previously? If yes, where/when?:

If your submission is not accepted, would you be open to presenting your topic in another part of the program? (e.g. lightning talk or unconference session)




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