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    <abstract>Frictive Policy Optimization treats friction in collaborative dialogue – misalignment, misunderstanding, repair – as an epistemic signal essential to common-ground construction, rather than noise to be minimized. However, FPO and its implementations have assumed shared perceptual contexts, where friction arises from differently interpreted propositions over the same scene, which we define as propositional asymmetry. We extend FPO to perceptual asymmetry, where participants hold asymmetric partial information and the same referring expression yields different denotations depending on whose information state grounds the reference. We evaluate this through cross-corpora analysis and LLM probing on referentially asymmetric dialogue tasks, primarily the HCRC MapTask. We find that FPO’s friction functional is empirically valid only when evaluated from within each participant’s information horizon: different landmark configurations produce qualitatively distinct grounding failure modes, with a small class of ambiguous configurations driving a disproportionate share of misunderstandings through trajectories that appear successful but silently diverge. The LLM probe confirms that having the right perspective matters more than having all perspectives: the informed single viewpoint outperforms omniscient access to both participants’ contexts. We propose two annotation refinements: subtype decomposition of pending grounding states and accommodation-aware alignment classification.</abstract>
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%0 Conference Proceedings
%T From Propositional to Perceptual Asymmetry: Extending FPO to Asymmetric Partial Information Dialogue
%A Zhu, Yifan
%A Rim, Kyeongmin
%A Pustejovsky, James
%Y Choi, Jinho D.
%Y Chen, Yun-Nung
%Y Funakoshi, Kotaro
%Y Emami, Ali
%S Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2026
%8 August
%I Association for Computational Linguistics
%C Atlanta, Georgia, USA
%F zhu-etal-2026-propositional
%X Frictive Policy Optimization treats friction in collaborative dialogue – misalignment, misunderstanding, repair – as an epistemic signal essential to common-ground construction, rather than noise to be minimized. However, FPO and its implementations have assumed shared perceptual contexts, where friction arises from differently interpreted propositions over the same scene, which we define as propositional asymmetry. We extend FPO to perceptual asymmetry, where participants hold asymmetric partial information and the same referring expression yields different denotations depending on whose information state grounds the reference. We evaluate this through cross-corpora analysis and LLM probing on referentially asymmetric dialogue tasks, primarily the HCRC MapTask. We find that FPO’s friction functional is empirically valid only when evaluated from within each participant’s information horizon: different landmark configurations produce qualitatively distinct grounding failure modes, with a small class of ambiguous configurations driving a disproportionate share of misunderstandings through trajectories that appear successful but silently diverge. The LLM probe confirms that having the right perspective matters more than having all perspectives: the informed single viewpoint outperforms omniscient access to both participants’ contexts. We propose two annotation refinements: subtype decomposition of pending grounding states and accommodation-aware alignment classification.
%U https://aclanthology.org/2026.sigdial-1.28/
%P 403-413

Markdown (Informal)

[From Propositional to Perceptual Asymmetry: Extending FPO to Asymmetric Partial Information Dialogue](https://aclanthology.org/2026.sigdial-1.28/) (Zhu et al., SIGDIAL 2026)

• From Propositional to Perceptual Asymmetry: Extending FPO to Asymmetric Partial Information Dialogue (Zhu et al., SIGDIAL 2026)

ACL

• Yifan Zhu, Kyeongmin Rim, and James Pustejovsky. 2026. From Propositional to Perceptual Asymmetry: Extending FPO to Asymmetric Partial Information Dialogue. In Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 403–413, Atlanta, Georgia, USA. Association for Computational Linguistics.