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03/29/2023
Evaluating NLG systems: A brief introduction
This year the International Conference on Natural Language Generation (I...
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12/08/2022
Implicit causality in GPT-2: a case study
This case study investigates the extent to which a language model (GPT-2...
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08/02/2021
Underreporting of errors in NLG output, and what to do about it
We observe a severe under-reporting of the different kinds of errors tha...
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06/16/2021
Automatic Construction of Evaluation Suites for Natural Language Generation Datasets
Machine learning approaches applied to NLP are often evaluated by summar...
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03/11/2021
Preregistering NLP Research
Preregistration refers to the practice of specifying what you are going ...
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02/02/2021
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
We introduce GEM, a living benchmark for natural language Generation (NL...
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06/15/2020
On the use of human reference data for evaluating automatic image descriptions
Automatic image description systems are commonly trained and evaluated u...
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08/23/2019
Neural data-to-text generation: A comparison between pipeline and end-to-end architectures
Traditionally, most data-to-text applications have been designed using a...
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07/06/2017
Cross-linguistic differences and similarities in image descriptions
Automatic image description systems are commonly trained and evaluated o...
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04/13/2017
Room for improvement in automatic image description: an error analysis
In recent years we have seen rapid and significant progress in automatic...
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06/20/2016
Pragmatic factors in image description: the case of negations
We provide a qualitative analysis of the descriptions containing negatio...
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05/19/2016
Stereotyping and Bias in the Flickr30K Dataset
An untested assumption behind the crowdsourced descriptions of the image...
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04/30/2015
