There are other, somewhat less related, ways to use feedback during dialogue for learning, notably for collecting knowledge to answer questions (Mazumder et al., 2018;Hixon et al., 2015;Pappu and Rudnicky, 2013), and more commonly in reinforcement learning settings, where the feedback is a scalar rather than the dialogue messages themselves (Levin et al., 2000;Schatzmann et al., 2006;Rieser and Lemon, 2011;Hong et al., 2019).
(Serban et al., 2017) employ user sentiment detection for reward shaping in their Alexa prize entry.