cs.HC · 2026-09-21 · No. 120

Human-Computer Interaction, 2026-09-21.

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

    Value-Sensitive Delegation in Everyday AI Agent Use: Evidence from OpenClaw

    Renkai Ma, Ruyuan Wan, Xuan Lu, Fan Yang, Chen Chen, Lingyao Li

    cs.HC · cs.AI

    Users increasingly delegate work to autonomous AI agents, yet evaluations typically measure task completion rather than the values users prioritize. Using Value Sensitive Design, we analyzed, with LLM assistance, 73,093 first-person Reddit posts about using OpenClaw, each for its human value, agent aspect, value fulfillment, and user outcome. The 21 values form six value groups, including Autonomous, Dependable, and Affordable Operation,...

    arxiv.org/abs/2609.22067 · PDF

  2. 02

    Gricea: An Open Science Platform for Conversational AI Research

    Nikhil Sharma, Yunlin Gong, Xinyang Cheng, Ziang Xiao

    cs.HC · cs.AI

    We need studies on conversational AI (CAI) at scale to understand human behavior and shape CAI design. However, fragmented reporting of systems and study configurations hinders replication, extension, and knowledge accumulation. We present Gricea, an open-science platform representing studies as configurable, deployable research artifacts that researchers can run, inspect, share, and reuse. Informed by a formative analysis of prior CAI...

    arxiv.org/abs/2609.22039 · PDF

  3. 03

    Touvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environments

    George Xi Wang, Xiangyu Li, Shaoyue Wen, Jiaqian Hu, Junan Xie, Yupeng Wang, Ziyue Shi, Qijun Chen, Maaike...

    cs.HC · cs.AI

    Blind and low-vision users often face challenges when locating and physically acquiring objects in unfamiliar indoor environments. Existing vision-language-model-based assistants can provide semantic descriptions but may introduce latency, hallucinations, and guidance that is poorly aligned with embodied action. We present Touvigation, a hands-free object acquisition system that combines vision-language understanding with persistent local...

    arxiv.org/abs/2609.21828 · PDF

  4. 04

    An Agentic Just-in-Time Adaptive Intervention System for Personalized Sleep Support: Proof-of-Concept Study with N of 1 Data

    Nick Rezaee, Chelsea Boccagno

    cs.HC · cs.AI

    Background: Just-in-time adaptive interventions (JITAIs) can use behavioral data to adapt support to changing contexts, but many rely on predefined rules and manual configuration. Objective: We developed a proof-of-concept sleep JITAI using an AI agent to review personal data, evaluate reminders, adapt interventions, and record decisions for human review. Methods: Running in Home Assistant on a configurable schedule, the agent follows a...

    arxiv.org/abs/2609.21805 · PDF

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