@inproceedings{scialom-etal-2020-toward,
title = "Toward Stance-based Personas for Opinionated Dialogues",
author = "Scialom, Thomas and
Tekiro{\u{g}}lu, Serra Sinem and
Staiano, Jacopo and
Guerini, Marco",
editor = "Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.findings-emnlp.238",
doi = "10.18653/v1/2020.findings-emnlp.238",
pages = "2625--2635",
abstract = "In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations. Still, the representation of such personas has thus far been limited to a fact-based representation (e.g. {``}I have two cats.{''}). We argue that these representations remain superficial w.r.t. the complexity of human personality. In this work, we propose to make a step forward and investigate stance-based persona, trying to grasp more profound characteristics, such as opinions, values, and beliefs to drive language generation. To this end, we introduce a novel dataset allowing to explore different stance-based persona representations and their impact on claim generation, showing that they are able to grasp abstract and profound aspects of the author persona.",
}
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<abstract>In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations. Still, the representation of such personas has thus far been limited to a fact-based representation (e.g. “I have two cats.”). We argue that these representations remain superficial w.r.t. the complexity of human personality. In this work, we propose to make a step forward and investigate stance-based persona, trying to grasp more profound characteristics, such as opinions, values, and beliefs to drive language generation. To this end, we introduce a novel dataset allowing to explore different stance-based persona representations and their impact on claim generation, showing that they are able to grasp abstract and profound aspects of the author persona.</abstract>
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%0 Conference Proceedings
%T Toward Stance-based Personas for Opinionated Dialogues
%A Scialom, Thomas
%A Tekiroğlu, Serra Sinem
%A Staiano, Jacopo
%A Guerini, Marco
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Findings of the Association for Computational Linguistics: EMNLP 2020
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F scialom-etal-2020-toward
%X In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations. Still, the representation of such personas has thus far been limited to a fact-based representation (e.g. “I have two cats.”). We argue that these representations remain superficial w.r.t. the complexity of human personality. In this work, we propose to make a step forward and investigate stance-based persona, trying to grasp more profound characteristics, such as opinions, values, and beliefs to drive language generation. To this end, we introduce a novel dataset allowing to explore different stance-based persona representations and their impact on claim generation, showing that they are able to grasp abstract and profound aspects of the author persona.
%R 10.18653/v1/2020.findings-emnlp.238
%U https://aclanthology.org/2020.findings-emnlp.238
%U https://doi.org/10.18653/v1/2020.findings-emnlp.238
%P 2625-2635
Markdown (Informal)
[Toward Stance-based Personas for Opinionated Dialogues](https://aclanthology.org/2020.findings-emnlp.238) (Scialom et al., Findings 2020)
ACL
- Thomas Scialom, Serra Sinem Tekiroğlu, Jacopo Staiano, and Marco Guerini. 2020. Toward Stance-based Personas for Opinionated Dialogues. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 2625–2635, Online. Association for Computational Linguistics.