cs.HC · 2026-06-25 · No. 34

Human-Computer Interaction, 2026-06-25.

3 new papers in cs.HC. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

3 entries
  1. 01

    Explainable Control Framework (XCF) based on Fuzzy Model-Agnostic Explanation and LLM Agent-Supported Interface

    Faliang Yin, Hak-Keung Lam, David Watson

    cs.HC · cs.AI · eess.SY

    Increasing demand for precise and reliable control in complex scenarios has led to the development of increasingly sophisticated controllers, including data-driven approaches employing closed box models and mathematically rigorous yet complex designs. This complexity highlights the needs for explainable control that can provide human-understandable insights into controller behavior. In this paper, an explainable control framework (XCF) along...

    arxiv.org/abs/2606.25941 · PDF

  2. 02

    FUTO Swipe: Layout-Agnostic Neural Swipe Decoding

    David Lee Miller, Aleksandras Kostarevas

    cs.HC · cs.LG

    Neural swipe decoders are typically tied to the keyboard they were trained on, requiring a new corpus and training run for each layout. In this report, we document our approach toward training models that can function on any contiguous mobile keyboard layout. At each point along the swipe, our encoder predicts whether the user is indicating a character and where on the keyboard that character lies. The keyboard layout is supplied at inference...

    arxiv.org/abs/2606.25247 · PDF

  3. 03

    Proactive Systems in HCI and AI: Concepts, Challenges, and Opportunities

    Nima Zargham, Sharon Ferguson, Jaisie Sin, Cosmin Munteanu, Anastasia Kuzminykh

    cs.HC · cs.AI

    The last few years have seen a significant rise in interest in highly autonomous and proactive systems, fueled by advances in AI. Systems that anticipate user needs, take initiative, and act without explicit user input. Such systems span a wide range of applications, from smart lighting that adapts to user activity to assistive robots that plan actions in advance to intelligent thermostats that learn routines and adjust environments...

    arxiv.org/abs/2606.25149 · PDF

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