Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics 2023
DOI: 10.18653/v1/2023.eacl-main.53
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Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Tasks

Kushal Chawla,
Weiyan Shi,
Jingwen Zhang
et al.

Abstract: Dialogue systems capable of social influence such as persuasion, negotiation, and therapy, are essential for extending the use of technology to numerous realistic scenarios. However, existing research primarily focuses on either task-oriented or open-domain scenarios, a categorization that has been inadequate for capturing influence skills systematically. There exists no formal definition or category for dialogue systems with these skills and data-driven efforts in this direction are highly limited. In this wo… Show more

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Cited by 4 publications
(3 citation statements)
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“…As discussed in prior work (Chawla et al, 2023), our analysis reflects upon the multi-faceted nature of the notion of success in negotiations, where observing a single dimension can be misleading. For example, when interacting with model S, the M p=S r=selfish agent seems to get high points for itself.…”
Section: Measuring Successmentioning
confidence: 99%
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“…As discussed in prior work (Chawla et al, 2023), our analysis reflects upon the multi-faceted nature of the notion of success in negotiations, where observing a single dimension can be misleading. For example, when interacting with model S, the M p=S r=selfish agent seems to get high points for itself.…”
Section: Measuring Successmentioning
confidence: 99%
“…Negotiation has been actively studied in diverse research areas, including Economics, Psychology, and Affective Computing (Carnevale and Pruitt, 2003). More recently, it has been studied as a social influence dialogue task for automated systems (Chawla et al, 2023). Automated systems capable of negotiating via realistic modes of communication, such as natural language, hold a huge potential in making social skills training more scalable and effective (Johnson et al, 2017).…”
Section: Automatic Negotiation Systemsmentioning
confidence: 99%
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