Skip to content

Ehud Reiter's Blog

Ehud's thoughts and observations about Natural Language Generation

  • Home
  • Blog Index
  • About
  • What is NLG
  • Publications
  • Resources
  • University
  • Contact

Category: building NLG systens

building NLG systens

Pain Points in Health NLG: Data, Evaluation, Safety

Jun 21, 2021Jun 21, 2021 ehudreiter1 Comment

I am really excited by the potential of NLG in healthcare. However, if we want to build real-world NLG systems which improve health, we need to surmount the “pain points” of data, evaluation, and safety.

building NLG systens

Check Out a New Dataset Before Using It

Jun 3, 2021 ehudreiterLeave a comment

If you are considering using a new dataset from a repository such as Kaggle, you should first check that the data in the dataset is of high quality and appropriate for your needs. A bit of “due diligence” at the beginning can stop you wasting lots of time and effort on an unsuitable data set.

building NLG systens

Content is King in NLG

Apr 22, 2021Apr 22, 2021 ehudreiter5 Comments

Texts produced by NLG systems need to communicate valuable, useful, and accurate information. I would love to see more research on content production and selection in NLG.

building NLG systens

Texts should be adapted to users

Apr 1, 2021Apr 1, 2021 ehudreiter2 Comments

If we want to use NLG to communicate information to all sorts of different people, then it would be really helpful if the NLG system can adapt its language to the reading skill, domain knowledge, emotional state, etc of the user. I think this kind of user adaptation is essential to achieving my vision of using NLG to humanise data.

building NLG systens

NLG Systems Must be Customisable

Feb 17, 2021Feb 17, 2021 ehudreiter2 Comments

Users want to be able to modify and customise NLG systems on their own, without needing to ask developers to make changes. Academic researchers mostly ignore this, which is a shame, since there are a lot of interesting and important challenges.

building NLG systens

Real-World Neural NLG

Dec 21, 2020 ehudreiter8 Comments

I was very impressed by a recent paper from a team at Facebook about a production-ready end-to-end neural NLG system. Especially interesting to me was the “engineering” approach to key issues such as accuracy, data collection, and latency.

  • LinkedIn
  • Twitter

Top Posts & Pages

  • ACL vs TACL Reviewing
  • Future of NLG evaluation: LLMs and high quality human eval?
  • "Will I Pass my PhD Viva"
  • Evaluating chatGPT
  • How to Validate Metrics
  • Publications
  • Bayesian vs Neural Networks
  • Good Papers are Hard to Publish
  • Blog Index
  • Unresponsive Authors and Experimental Flaws
Blog at WordPress.com.
  • Follow Following
    • Ehud Reiter's Blog
    • Join 83 other followers
    • Already have a WordPress.com account? Log in now.
    • Ehud Reiter's Blog
    • Customise
    • Follow Following
    • Sign up
    • Log in
    • Report this content
    • View site in Reader
    • Manage subscriptions
    • Collapse this bar