@InProceedings{sachan-xing:2017:starSEM,
  author    = {Sachan, Mrinmaya  and  Xing, Eric},
  title     = {Learning to Solve Geometry Problems from Natural Language Demonstrations in Textbooks},
  booktitle = {Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {251--261},
  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.},
  url       = {http://www.aclweb.org/anthology/S17-1029}
}