Keynote: Robustness and Scalability for Conversational AI

Even conversational systems have attracted a lot of attention recently, the current systems sometimes fail due to the errors from different components. This talk presents potential directions for improvement: 1) we first focus on learning language embeddings specifically for practical scenarios for better robustness, and 2) secondly we propose a novel learning framework for natural language understanding and generation on top of duality for better scalability. Both directions enhance the robustness and scalability of conversational systems, showing the potential of guiding future research areas.

Keynote: Knowledge-Grounded Social Conversational AI

Keynote: Language Grounding with Robots

We use language to refer to objects like “toast”, “plate”, and “table” and to communicate requests such as “Could you make breakfast?” In this talk, I will present work on computational methods to tie language to physical, grounded meaning. Robots are an ideal platform for such work because they can perceive and interact with the world. I will discuss dialog and learning strategies I have developed to enable robots to learn from their human partners, similar to how people learn from one another through interaction. I will present methods enabling robots to understand language referring expressions like “the heavy, metallic mug”, the first work showing that it is possible to learn to connect words to their perceptual properties in the visual, tactile, and auditory senses of a physical robot. I will also present a benchmark of human-human dialogs for cooperative navigation, as well as models for both navigation and end-to-end, agent-agent dialog execution trained on that benchmark.

Keynote: Recipes for building an open-domain chatbot

Keynote: Conversational Perspectives on Description and Explanation

Keynote: Recent work on label accuracy and dialog state tracking