Jose M. Alonso

Also published as: Jose Alonso


2023

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Some lessons learned reproducing human evaluation of a data-to-text system
Javier González Corbelle | Jose Alonso | Alberto Bugarín-Diz
Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems

This paper presents a human evaluation reproduction study regarding the data-to-text generation task. The evaluation focuses in counting the supported and contradicting facts generated by a neural data-to-text model with a macro planning stage. The model is tested generating sport summaries for the ROTOWIRE dataset. We first describe the approach to reproduction that is agreed in the context of the ReproHum project. Then, we detail the entire configuration of the original human evaluation and the adaptations that had to be made to reproduce such an evaluation. Finally, we compare the reproduction results with those reported in the paper that was taken as reference.

2020

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2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence
Jose M. Alonso | Alejandro Catala
2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence

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Towards Harnessing Natural Language Generation to Explain Black-box Models
Ettore Mariotti | Jose M. Alonso | Albert Gatt
2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence

The opaque nature of many machine learning techniques prevents the wide adoption of powerful information processing tools for high stakes scenarios. The emerging field eXplainable Artificial Intelligence (XAI) aims at providing justifications for automatic decision-making systems in order to ensure reliability and trustworthiness in the users. For achieving this vision, we emphasize the importance of a natural language textual modality as a key component for a future intelligent interactive agent. We outline the challenges of XAI and review a set of publications that work in this direction.

2019

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Proceedings of the 1st Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI 2019)
Jose M. Alonso | Alejandro Catala
Proceedings of the 1st Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI 2019)

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Paving the way towards counterfactual generation in argumentative conversational agents
Ilia Stepin | Alejandro Catala | Martin Pereira-Fariña | Jose M. Alonso
Proceedings of the 1st Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI 2019)

2018

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Meteorologists and Students: A resource for language grounding of geographical descriptors
Alejandro Ramos-Soto | Ehud Reiter | Kees van Deemter | Jose Alonso | Albert Gatt
Proceedings of the 11th International Conference on Natural Language Generation

We present a data resource which can be useful for research purposes on language grounding tasks in the context of geographical referring expression generation. The resource is composed of two data sets that encompass 25 different geographical descriptors and a set of associated graphical representations, drawn as polygons on a map by two groups of human subjects: teenage students and expert meteorologists.

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Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)
Jose M. Alonso | Alejandro Catala | Mariët Theune
Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)

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Supporting Content Design with an Eye Tracker: The Case of Weather-based Recommendations
Alejandro Catala | Jose M. Alonso | Alberto Bugarin
Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)

2017

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Proceedings of the 10th International Conference on Natural Language Generation
Jose M. Alonso | Alberto Bugarín | Ehud Reiter
Proceedings of the 10th International Conference on Natural Language Generation

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Linguistic Description of Complex Phenomena with the rLDCP R Package
Jose Alonso | Patricia Conde-Clemente | Gracian Trivino
Proceedings of the 10th International Conference on Natural Language Generation

Monitoring and analysis of complex phenomena attract the attention of both academy and industry. Dealing with data produced by complex phenomena requires the use of advance computational intelligence techniques. Namely, linguistic description of complex phenomena constitutes a mature research line. It is supported by the Computational Theory of Perceptions grounded on the Fuzzy Sets Theory. Its aim is the development of computational systems with the ability to generate vague descriptions of the world in a similar way how humans do. This is a human-centric and multi-disciplinary research work. Moreover, its success is a matter of careful design; thus, developers play a key role. The rLDCP R package was designed to facilitate the development of new applications. This demo introduces the use of rLDCP, for both beginners and advance developers, in practical use cases.

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An Essay on Self-explanatory Computational Intelligence: A Linguistic Model of Data Processing Systems
Jose M. Alonso | Gracian Trivino
Proceedings of the 1st Workshop on Explainable Computational Intelligence (XCI 2017)