Further Advances in Open Domain Dialog Systems in the Third Alexa Prize Socialbot Grand Challenge

By Raefer Gabriel, Yang Liu, Anna Gottardi, Mihail Eric, Anju Khatri, Anjali Chadha, Qinlang Chen, Behnam Hedayatnia, Pankaj Rajan, A. Binici and 7 more. 2020

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BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage (2022, background): “The promise of such an approach is that the distribution of data will more closely match those organic users’ desires, rather than decided by the researchers themselves when creating datasets (Gabriel et al., 2020; Roller et al., 2020; Shuster et al., 2021b; Ouyang et al., 2022).”
Human Evaluation of Conversations is an Open Problem: comparing the sensitivity of various methods for evaluating dialogue agents (2022, background): “Evaluation by deployment can be successful (Gabriel et al., 2020; Shuster et al., 2020), where behavioral metrics such as the amount of conversation time per user or retention rate can serve as a proxy for interestingness and engagingness metrics.”
Learning from data in the mixed adversarial non-adversarial case: Finding the helpers and ignoring the trolls (2022, background): “The promise of this approach is that the distribution of data will more closely match those organic users’ desires, rather than decided by the researchers themselves when creating datasets (Gabriel et al., 2020; Roller et al., 2020; Shuster et al., 2020; Ouyang et al., 2022).”