Ruptures represent common albeit critical moments in interaction where relational alignment breaks down, making them essential for evaluating AI where trust and engagement matter most. In a scenario-driven empirical study, we examined the performance of three LLMs at identifying and resolving ruptures across 21 mental...
Jeongah Lee, Joy Qiuyue Zhong, Drishti Goel et al.· 0 citations
Gratitude technologies support well-being by prompting reflection on what people appreciate. But gratitude does not serve the same purpose in every circumstance: as life situations change, so does what people seek from it, and whether it feels appropriate at all. To understand how technology can adapt to and support su...
Joy Qiuyue Zhong, Jeongah Lee, Drishti Goel et al.· 0 citations
AI companions can purportedly adopt racial personas, raising questions about how they represent identity and how users interpret these portrayals. We combined an algorithmic audit of race-coded AI personas with interviews with 12 companion users who interacted with a probe. Our audit revealed systematic differences, su...
Wang Claire, J. Shi, Agam Goyal et al.· 0 citations
This work presents the first large-scale empirical comparison of AI-agent and human online communities, analyzing 73,899 Moltbook and 189,838 Reddit posts across five matched communities.
Agam Goyal, Olivia Pal, Hari Sundaram et al.· arXiv.org· 11 citations
CareMirror is built, an envisioned caregiver wellbeing ecosystem with interconnected caregiver- and clinician-facing interfaces for longitudinal reflection, personalized support, and caregiver-controlled sharing with clinical care.
J. Shi, Ethan D. Nguyen, Drishti Goel et al.· 0 citations
A co-design study where 14 participants redesigned Google and Apple Health interfaces using Figma Make, finding conversational AI designs converged around chat-window conventions and implications for preserving agency and flexible user-directed interfaces.
Karthik S. Bhat, Vidhi Shah, V. Agnihotri et al.· 0 citations
PeerPen, a writing assistance tool embedded within a Reddit-like interface, supporting two main features: draft generation and revision of user-written responses, is built and it is found that PeerPen reduced the burden of composing responses and increased confidence in offering support.
The Nimblemind Multi-Agent System is developed, an evidence-linked, rubric-grounded pipeline for automated heart-failure feature engineering, and evaluation was limited to a single-institution cohort and external validation is needed, demonstrating the feasibility of automated, auditable feature engineering for complex...
The findings suggest that open-source models, when trained with community-derived preference signals, can support high-quality mental health support assistance while offering a more privacy-preserving alternative for sensitive support contexts.
J. Kim, Maya Ajit, S. Gong et al.· arXiv.org· 4 citations
A spectrum-placement task inspired by the social party game Wavelength is developed, which suggests that TUX provides a measurable behavioral signal of human--LLM tacit understanding, while revealing the limits of profile-based conditioning for capturing deeper representational alignment.
Yue-Shen Li, Han-Yi Min, Vedant Das Swain et al.· arXiv.org· 0 citations
The feasibility of using a configurable, source-grounded extraction workflow to convert fragmented oncology documentation into reusable structured data is supported.
Daniel Kang, Michelle Hu, Soorya Ram Shimgekar et al.· 0 citations
The NimbleMind Multi-Agent System (nMAS) is evaluated, a configurable workflow that separates clinician-defined field specifications from extraction models and returns report-level predictions with source-linked evidence within a clinician-reviewable workflow.
Yu-Fan Wang, Anit Kumar Sahu, Y. Ng et al.· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
