How I Review Papers
A few comments on how I review papers (what I actually do, not what I am supposed to do), and associated advice for authors.
Lexical Choice Needs Machine Learning!
Lexical choice is an area of NLG which really needs machine-learning and data-based techniques.
Academic Researchers Should be Scouts and Explorers
Perhaps being somewhat idealistic, I think academic researchers should act as “scouts” exploring unknown research terrain
Notes from a Dev Conf: Sensible Attitude to Trendy AI Tech, Arria Presentations
I went to my first developers conference last week and was impressed, not least by the sensible attitude towards deep learning and other trendy AI technology.
Use Good Engineering Methodology When Building NLG Systems!
Good software engineering is criticial when building NLG systems, including requirements analysis, design, testing, and support.
Please Use Two-Tailed P Values!
If you are writing a scientific paper which presents statistics, please use two-tailed p values unless you **really** know what you are doing.
How do I Learn about NLG?
Some suggestions for people who are new to NLG and want to learn more about it.
Dealing with Edge Cases in NLG
I give some high-level advice on handling edge cases in NLG. As with any software system, most of the effort in building NLG systems usually goes into handling edge cases.
Goodbye to a Synagogue
I was very sad to hear that the Jewish synagogue in the Scottish town of Dundee is likely to close
Should I Use Deep Learning?
There is a lot of hype around deep learning. especially at business-oriented AI events. I suggest some questions to think about for companies who are considering using DL.
Ehud Reiter's Blog 