ADAPTIC: Adapting Dialog and Pragmatic Traits in Context
TL;DR
This workshop proposes a paradigm shift toward designing context-specific CUIs that actively support communicative success through pragmatic cues, and brings together perspectives from HCI and social sciences to explore how users appropriate conversational AI across domains.
Abstract
The rise of LLMs has enabled CUIs to increasingly mimic human social and conversational cues, e.g., tone of voice and emotional expressions. However, this mimicry usually lacks strategic communicative intent, placing the cognitive burden of mutual understanding on the user. At the same time, CUIs based on general-purpose, task-agnostic LLMs are being deployed across varied domains with distinct, context-specific conversational needs, including, e.g., healthcare, education, and journalism. Therefore, there is a growing need to transition from arbitrary, domain-agnostic generation of pragmatic cues to strategic adaptation of both visual and linguistic interface features. This workshop proposes a paradigm shift toward designing context-specific CUIs that actively support communicative success through pragmatic cues. Bringing together perspectives from HCI and social sciences, we will explore how users appropriate conversational AI across domains. Through cross-disciplinary dialogue, the workshop aims to establish a shared vocabulary, identify domain-specific challenges, and lay the groundwork for future collaboration.