Meta wants to fix broken Wikipedia citations for good

AI could make Wikipedia a more reliable source, Meta says

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Wikipedia may be the go-to resource on almost everything these days, but according to Meta, it’s filled with dodgy, inaccurate citations.

But don’t worry, the company says its AI is here to help, having developed Sphere, a model capable of automatically scanning hundreds of thousands of citations at once to check whether they truly support the corresponding claims.

Meta claims it created a new dataset of 134 million public web pages as a knowledge source for the model, which says is “an order of magnitude larger and significantly more intricate than ever used for this sort of research”.

Meta citations

Sphereuses open web data rather than traditional, proprietary search engines such asGoogle, and has already compiled 134 million documents from across the web.

Built usingCCNet, a variant of Common Crawl, Meta says Sphere will help other AI researchers working on knowledge retrieval projects.

Meta says the eventual goal of the project is to build a platform to help Wikipedia editors systematically spot citation issues and quickly fix the citation or correct the content of the corresponding article at scale.

The company is not partnering with Wikimedia on the project, which is still in the research phase and is not being used to automatically update any content on Wikipedia.

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The tool reportedly calls attention to questionable citations, allowing human editors to evaluate the cases most likely to be flawed without having to sift through thousands of properly cited statements.

If a citation seems irrelevant, Meta says its model will suggest a more applicable source, even pointing to the specific passage that supports the claim.

You can grab the source code for the project on GitHubhere, and interested parties can also read a full write-up of the project’s findingshereor access the demohere.

Will McCurdy has been writing about technology for over five years. He has a wide range of specialities including cybersecurity, fintech, cryptocurrencies, blockchain, cloud computing, payments, artificial intelligence, retail technology, and venture capital investment. He has previously written for AltFi, FStech, Retail Systems, and National Technology News and is an experienced podcast and webinar host, as well as an avid long-form feature writer.

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