Extended Abstract

Analysis of Language Change in Collaborative Instruction Following

Authors
  • Anna Effenberger (Cornell University)
  • Eva Yan (City University of New York)
  • Rhia Singh (CUNY Macaulay Honors College)
  • Alane Suhr (Cornell University)
  • Yoav Artzi (Cornell University)

Abstract

We analyze language change over time in a collaborative, goal-oriented instructional task, where utility-maximizing participants form conventions and increase their expertise. Prior work studied such scenarios mostly in the context of reference games, and consistently found that language complexity is reduced along multiple dimensions, such as utterance length, as conventions are formed. In contrast, we find that, given the ability to increase instruction utility, instructors increase language complexity along these previously studied dimensions to better collaborate with increasingly skilled instruction followers.

Keywords: instruction following, collaboration, interaction, language change, language grounding, convention formation

How to Cite:

Effenberger, A., Yan, E., Singh, R., Suhr, A. & Artzi, Y., (2022) “Analysis of Language Change in Collaborative Instruction Following”, Society for Computation in Linguistics 5(1), 194-202. doi: https://doi.org/10.7275/5zye-wh63

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Published on
01 Feb 2022