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I know people have been having trouble adapting these kinds of generative techniques to text. Do you know of anyone making interesting progress there?

heydenberk 7y ago
I put your question in talktotransformer.com and got this response: I know people have been having trouble adapting these kinds of generative techniques to text. Do you know of anyone making interesting progress there? It is difficult to make progress in the field of generative methods with text alone - it takes effort and creativity to get a generative system working. A big part of our research focuses on generating sequences which correspond to handwritten data, and to improving on that method we have developed generative techniques which allow us to generate a large range of novel sequences. Our work is still small, but we are not stopping there, in fact our next major research project is to generate novel sequences for novel languages. What I see is that we are still in an early stage when it comes to the technology used in generative methods to create new words, but I suspect this is due to a combination of factors. First and foremost is the fact that the techniques we've developed to generate novel sequences are highly specialized in a particular kind of context - we are not going to create random numbers or sequences because that just doesn't work. Generating a word, for example, uses very specific computational principles and can only be done if you are aware of the context in which it is being generated (or "determined" as the linguists would say). Even so, the general principle has been around so long, that one could quite easily create several different methods to create.
- gwern 7y ago
  GPT-2 is, however, not adversarial at all, and that might be part of why it rambles and lacks consistency or much of a 'point'.
  - ReDeiPirati 7y ago
    +1. Also, the author of this article wrote a terrific article on GPT-2 as well. I'll definitively recommend you to check it out if you are interested in the latest breakthrough of text generation: https://blog.floydhub.com/gpt2/ https://blog.floydhub.com/gpt2/
lettergram 7y ago
Yes! https://medium.com/capital-one-tech/why-you-dont-necessarily-need-data-for-data-science-48d7bf503074 https://medium.com/capital-one-tech/why-you-dont-necessarily... GANs simply try to replicate a set of features - you can think of this as images or text. Variations in the GAN designs will be present, but the general principles are the same.

heydenberk 7y ago

I put your question in talktotransformer.com and got this response: I know people have been having trouble adapting these kinds of generative techniques to text. Do you know of anyone making interesting progress there? It is difficult to make progress in the field of generative methods with text alone - it takes effort and creativity to get a generative system working. A big part of our research focuses on generating sequences which correspond to handwritten data, and to improving on that method we have developed generative techniques which allow us to generate a large range of novel sequences. Our work is still small, but we are not stopping there, in fact our next major research project is to generate novel sequences for novel languages. What I see is that we are still in an early stage when it comes to the technology used in generative methods to create new words, but I suspect this is due to a combination of factors. First and foremost is the fact that the techniques we've developed to generate novel sequences are highly specialized in a particular kind of context - we are not going to create random numbers or sequences because that just doesn't work. Generating a word, for example, uses very specific computational principles and can only be done if you are aware of the context in which it is being generated (or "determined" as the linguists would say). Even so, the general principle has been around so long, that one could quite easily create several different methods to create.

gwern 7y ago
GPT-2 is, however, not adversarial at all, and that might be part of why it rambles and lacks consistency or much of a 'point'.
- ReDeiPirati 7y ago
  +1. Also, the author of this article wrote a terrific article on GPT-2 as well. I'll definitively recommend you to check it out if you are interested in the latest breakthrough of text generation: https://blog.floydhub.com/gpt2/ https://blog.floydhub.com/gpt2/

lettergram 7y ago

Yes! https://medium.com/capital-one-tech/why-you-dont-necessarily-need-data-for-data-science-48d7bf503074 https://medium.com/capital-one-tech/why-you-dont-necessarily... GANs simply try to replicate a set of features - you can think of this as images or text. Variations in the GAN designs will be present, but the general principles are the same.