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It's hard to get a sense for how cherry-picked the examples are with such a limited set of neural-generated articles exposed for our inspection. With that said
by jaytaylor 7y ago
It's hard to get a sense for how cherry-picked the examples are with such a limited set of neural-generated articles exposed for our inspection.
With that said, this is definitely interesting work! I've researched, published, and presented (at the Web Conference in SF, just last month) on using NLP with Discourse Analysis to detect lies and deception in product reviews [0]. I wonder if improvements in accuracy could be achieved by using both techniques in concert.
[0] https://jaytaylor.com/WWW19COMPANION-138--An_Anatomy_of_a_Lie-Discourse_Patterns_in_Customer_Complaints_Deception_Dataset.pdf https://jaytaylor.com/WWW19COMPANION-138--An_Anatomy_of_a_Li...
- schmmd 7y agoYou can generate your own examples with the "Generate" button. It will fill in that field based on generated text using the other fields as input. For example, you could clear all the fields, enter a headline, and generate an article for that headline.
- jaytaylor 7y agoOh, thanks for the info. I tried on mobile and it wasn't clear this is possible. I'll play around with it more Cheers!