Multi-Modal Open-Domain Dialogue

Understand

Recent work in open-domain conversational agents has demonstrated that significant improvements in model engagingness and humanness metrics can be achieved via massive scaling in both pre-training data and model size (Adiwardana et al., 2020; Roller et al., 2020).

• However, if we want to build agents with human-like abilities, we must expand beyond handling just text.
• A particularly important topic is the ability to see images and communicate about what is perceived.
• With the goal of engaging humans in multi-modal dialogue, we investigate combining components from state-of-the-art open-domain dialogue agents with those from state-of-the-art vision models.