@inproceedings{sieker-zarriess-2026-misalignments,
title = "Misalignments in Common Ground as a Bridge Between Pragmatic Theory and {LLM} Evaluation",
author = "Sieker, Judith and
Zarrie{\ss}, Sina",
editor = "Bernard, Timoth{\'e}e and
Chersoni, Emmanuele and
Rambelli, Giulia",
booktitle = "Proceedings of the Third Workshop on the Bridges and Gaps between Formal and Computational Linguistics ({B}ri{G}ap-3)",
month = jul,
year = "2026",
address = "Paris, France",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.brigap-1.8/",
pages = "74--81",
abstract = "In this position paper, we argue that misalignments in common ground are not marginal failures of communication, but central diagnostic moments for pragmatic competence, and should therefore play a key role in the evaluation of Large Language Models (LLMs). Evaluating how models respond to such instances of mismatched or incomplete understanding moves beyond surface fluency and correctness, targeting pragmatic competence at a deeper, interactional level. At the same time, misalignments provide controlled settings for testing linguistic theories of common ground, repair, or accommodation {--} areas that are often difficult to investigate in human communication. We argue that this dual role makes misalignments a natural bridge between pragmatic theory and LLM evaluation."
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%0 Conference Proceedings
%T Misalignments in Common Ground as a Bridge Between Pragmatic Theory and LLM Evaluation
%A Sieker, Judith
%A Zarrieß, Sina
%Y Bernard, Timothée
%Y Chersoni, Emmanuele
%Y Rambelli, Giulia
%S Proceedings of the Third Workshop on the Bridges and Gaps between Formal and Computational Linguistics (BriGap-3)
%D 2026
%8 July
%I Association for Computational Linguistics
%C Paris, France
%F sieker-zarriess-2026-misalignments
%X In this position paper, we argue that misalignments in common ground are not marginal failures of communication, but central diagnostic moments for pragmatic competence, and should therefore play a key role in the evaluation of Large Language Models (LLMs). Evaluating how models respond to such instances of mismatched or incomplete understanding moves beyond surface fluency and correctness, targeting pragmatic competence at a deeper, interactional level. At the same time, misalignments provide controlled settings for testing linguistic theories of common ground, repair, or accommodation – areas that are often difficult to investigate in human communication. We argue that this dual role makes misalignments a natural bridge between pragmatic theory and LLM evaluation.
%U https://aclanthology.org/2026.brigap-1.8/
%P 74-81
Markdown (Informal)
[Misalignments in Common Ground as a Bridge Between Pragmatic Theory and LLM Evaluation](https://aclanthology.org/2026.brigap-1.8/) (Sieker & Zarrieß, BriGap 2026)
ACL