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.
CITATION STYLE
Effenberger, A., Yan, E., Singh, R., Suhr, A., & Artzi, Y. (2021). Analysis of Language Change in Collaborative Instruction Following. In Findings of the Association for Computational Linguistics, Findings of ACL: EMNLP 2021 (pp. 2803–2811). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.findings-emnlp.239
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