Alignment-Based Compositional Semantics for Instruction Following
Jacob Andreas, Dan Klein · 2015
This paper describes an alignment-based model for interpreting natural language instructions in context.We approach instruction following as a search over plans, scoring sequences of actions conditioned on structured observations of text and the environment.By explicitly modeling both the low-level compositional structure of individual actions and the high-level structure of full plans, we are able to learn both grounded representations of sentence meaning and pragmatic constraints on interpretation.To demonstrate the model's flexibility, we apply it to a diverse set of benchmark tasks.On every task, we outperform strong task-specific baselines, and achieve several new state-of-the-art results.