human-interaction

Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing

Human-AI Interaction

We explore how machine learning systems can interact with humans effectively. This includes being able to converse with humans through dialogues, as well as proactively collaborate with and learn from humans during decision making.

Learning Structural Edits via Incremental Tree Transformations

An Imitation Game for Learning Semantic Parsers from User Interaction

Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning

Model-based Interactive Semantic Parsing: A Unified Framework and A Text-to-SQL Case Study

Reinforced Dynamic Reasoning for Conversational Question Generation

IEC: Towards Interest-Eliciting Neural Conversational Agents