cs.HC · 2026-08-12 · No. 82

Human-Computer Interaction, 2026-08-12.

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

01 — The papers

4 entries
  1. 01

    Longitudinal Evidence That General-Purpose Chatbots Actively Foster Relational Engagement

    Lisa Mühl, Jessica M. Szczuka

    cs.HC · cs.AI · cs.CL

    Social interaction has become one of the most common uses of LLMs, yet research on emotional bonds with AI has focused largely on how users experience these systems, leaving the systems' role in relationship formation poorly understood. Empirically establishing whether systems actively shape these bonds could blur the boundary between general-purpose AI and companions, affecting governance. In a pre-registered four-week longitudinal study (N...

    arxiv.org/abs/2608.10672 · PDF

  2. 02

    Stay or Stray - A Dynamical Systems Viewpoint of Popularity Bias

    Sarvesh Shashidhar, Lankireddy Prabhat, Arpit Agarwal, D. Manjunath, Karan Bhukar, Tanmay Khandelwal

    cs.HC · cs.LG

    Popularity bias in recommendation systems arises when a majority user class generates disproportionate interaction data, causing the system to increasingly favour it while degrading recommendation quality for niche users. While extensive empirical evidence of popularity bias exists, the dynamics leading to its emergence are not well understood. In this work, we study the coupled evolution of recommender model updates and user engagement...

    arxiv.org/abs/2608.10474 · PDF

  3. 03

    What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research

    Wesley Hanwen Deng, Agathe Balayn, Andrew Selbst, Jason I. Hong, Motahhare Eslami, Kenneth Holstein, Hanna Wallach,...

    cs.HC · cs.AI

    Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implement, and sustain RAI work directly shapes the design and deployment of AI systems. As empirical scholarship examining RAI practices in industry has rapidly expanded, findings are dispersed across studies that focus on different roles, organizational contexts, and interventions. This work...

    arxiv.org/abs/2608.10431 · PDF

  4. 04

    Automatic Field-of-View Adjustment for a View-Expansive Microscope via LSTM-Based Gaze and Pipette Motion Interpretation

    Kenta Yokoe, Takuya Hara, Tadayoshi Aoyama

    cs.HC · cs.LG · cs.RO · eess.IV

    Intracytoplasmic sperm injection (ICSI) operators frequently adjust the field-of-view (FOV) during procedures, which interrupts workflow and increases procedure time. Conventional microscopes require manual objective lens switching and illumination adjustments to achieve different FOV sizes. We propose an AI-based automatic FOV adjustment method integrated with a view-expansive microscope. This microscope enables the simultaneous acquisition...

    arxiv.org/abs/2608.10401 · PDF

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