Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills

Understand

Being engaging, knowledgeable, and empathetic are all desirable general qualities in a conversational agent.

• Previous work has introduced tasks and datasets that aim to help agents to learn those qualities in isolation and gauge how well they can express them.
• But rather than being specialized in one single quality, a good open-domain conversational agent should be able to seamlessly blend them all into one cohesive conversational flow.
• In this work, we investigate several ways to combine models trained towards isolated capabilities, ranging from simple model aggregation schemes that require minimal additional training, to various forms of multi-task training that encompass several skills at all training stages.