Year: 2017
Type: conference-paper
Abstract: Humans as well as animals are good at imitation.Inspired by this, the learning by demonstration view of machine learning learns to perform a task from detailed example demonstrations.In this paper, we introduce the task of question answering using natural language demonstrations where the question answering system is provided with detailed demonstrative solutions to questions in natural language.As a case study, we explore the task of learning to solve geometry problems using demonstrative solutions available in textbooks.We collect a new dataset of demonstrative geometry solutions from textbooks and explore approaches that learn to interpret these demonstrations as well as to use these interpretations to solve geometry problems.Our approaches show improvements over the best previously published system for solving geometry problems.
DOI: 10.18653/v1/s17-1029
Authors: Mrinmaya Sachan, Eric Xing
Institution: Carnegie Mellon University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W2740314591