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Ehud's thoughts and observations about Natural Language Generation

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Tag: Machine Learning

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Hallucination in Neural NLG

Nov 12, 2018Nov 12, 2018 ehudreiter16 Comments

Many neural NLG systems “hallucinate” non-existent or incorrect content. This is a major problem, since such hallucination is unacceptable in many (most?) NLG use cases. Also BLEU and related metrics do not detect hallucination well, so researchers who rely on such metrics may be misled about the quality of their system.

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Use Proper Baselines!

Aug 30, 2018 ehudreiter1 Comment

Unfortunately I suspect many researchers make their results looks better by using poor baselines. I give some thoughts on this, based on a recent discussion with a PhD student.

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Many Papers on Machine Learning in NLP are Scientifically Dubious

Jun 6, 2018 ehudreiter1 Comment

In response to a previous blog, many people expressed concerns to me about the quality of many papers they saw on ML in NLP. I summarise some of these concerns, which are worrying.

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Learning does not require evaluation metrics

May 30, 2018May 30, 2018 ehudreiter3 Comments

I was recently asked if machine learning requires evaluation metrics. The answer is no, and the fact that people are asking such questions suggests that some newcomers to the field may have a limited perspective on NLP research methodology.

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Lexical Choice Needs Machine Learning!

Mar 19, 2018 ehudreiter7 Comments

Lexical choice is an area of NLG which really needs machine-learning and data-based techniques.

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Notes from a Dev Conf: Sensible Attitude to Trendy AI Tech, Arria Presentations

Feb 26, 2018 ehudreiterLeave a comment

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.

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Should I Use Deep Learning?

Dec 11, 2017Dec 11, 2017 ehudreiter1 Comment

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.

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Embedding Machine Learning in a Rules-Based NLG System

Oct 16, 2017Oct 18, 2017 ehudreiterLeave a comment

I think we should use rules to make simple high-value decisions, and learning to make complex low-value decisions, within an architecture where ML decision makers are embedded in a rules-based framework.

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Does Quality Matter in Training Data?

Sep 1, 2017 ehudreiter2 Comments

I am concerned that some people seem to ignore quality issues in training data.

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Response to Goldberg’s Blog on Deep Learning for NLG

Jun 19, 2017Jan 3, 2018 ehudreiter11 Comments

My response to Goldberg’s “adversarial review” of some research on using deep learning in NLG

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