cs.HC · 2026-07-02 · No. 41

Human-Computer Interaction, 2026-07-02.

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

    SenseWalk: Agent-Based Semantic Trajectory Simulation Powered by Large Language Models in Zoned Environments

    Ziyue Lin, Xinhang Xie, Kangyi Wang, Siming Chen

    cs.HC · cs.AI

    Semantic trajectory analysis has recently emerged as an approach for modeling human movement by capturing implicit patterns and behaviors through semantic information (e.g., visitors' profiles and goals) beyond raw spatial paths to better understand why people move in certain ways. However, analyzing semantic trajectories in real-world scenarios remains challenging, as collecting high-quality data is costly and often lacks rich semantic...

    arxiv.org/abs/2607.00989 · PDF

  2. 02

    Understanding How Humans Inject Knowledge into Machine Learning Workflows through Visual Analytics

    Yiwen Xing, Philip Beaucamp, Joyraj Chakraborty, Afrah Farea, Yuanzhe Jin, Saiful Khan, Gennady Andrienko, Natalia...

    cs.HC · cs.LG

    Visual analytics (VA) plays an increasingly important role in supporting machine learning (ML) workflows. In the field of visualization, such approaches and techniques are referred to as VIS4ML. While ML models are mostly learned automatically, the corresponding ML workflows receive a variety of human inputs, such as data labelling, feature engineering, model architecture designing, hyper-parameter tuning, and so on. In this work, we surveyed...

    arxiv.org/abs/2607.00969 · PDF

  3. 03

    AI, Trust, and Teaming: The Humans-as-Handlers Approach for Autonomous and Opaque AI Systems

    Nathan G. Wood

    cs.HC · cs.AI · cs.CY · cs.ET · eess.SY

    Artificial intelligence (AI) is becoming ubiquitous, and across domains, increasingly autonomous systems are carrying out tasks which raise significant ethical and legal challenges which demonstrate a need for strong human-machine teams rooted in trust. In this article, I argue that within highly impactful areas (such as medicine or warfighting) there are grounds for us initially treating autonomous and opaque systems as relevantly analogous...

    arxiv.org/abs/2607.00523 · PDF

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