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61 - Neural Text Generation in Stories, with Elizabeth Clark and Yangfeng Ji

NLP Highlights

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The Uptake of Natural Language Generation

I was at Knackle last month and I saw many papers talking about generation test string. How can we go from sort of traditional methods to these models where you have maybe tons of story data, but you're not really utilizing any of it in a particularly interesting way? It seems like if you can get a good entity language model and have a good way to get better contextualized word representations that are informed by this discrete notion of entities, maybe you should just have a better animal, right? Does that make sense?Yeah, I think that makes a lot of sense. And I'm excited about the creativity space, like moving away from like how do we support people and test like great starter

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