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- W4304080247 abstract "In task-oriented dialog agents, the initial user experience sets the tone for future interactions and plays a major role in whether the user returns to the system. But with the diversity of human interaction, these systems often struggle with more complex requests that differ significantly from their training data creating an unpleasant and frustrating user experience. In this work, we formulate an alternative and less resource-intensive approach to improving user experience by implicitly conveying possible user action in system responses. We make use of real-world data to test and support our claims, showing that a significant share of the users made use of such information. Additionally, we extend this to product recommendation as a way to anchor the interaction to well-established flows, we then perform data analysis that shows that close to a third of the users tried benefited from such recommendations. We conclude with an overview of the plans for my Ph.D. thesis and how these findings line up with our goal of producing an ideal agent." @default.
- W4304080247 created "2022-10-10" @default.
- W4304080247 creator A5029700943 @default.
- W4304080247 date "2022-10-10" @default.
- W4304080247 modified "2023-09-28" @default.
- W4304080247 title "The First Impression" @default.
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- W4304080247 doi "https://doi.org/10.1145/3503161.3548760" @default.
- W4304080247 hasPublicationYear "2022" @default.
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