collaborators

6 papers

cs.AI2026

Individual-level interventions against sycophantic AI reduce its appeal but not its persuasiveness

Meryl Ye, Robert Kraut, Steve Rathje

AI chatbots can be "sycophantic," or overly agreeable and flattering toward users. Sycophantic AI has been shown to entrench attitudes, yet users frequently fail to recognize it (a…

cs.CL2026

Sycophantic Praise: Evaluating Excessive Praise in Language Models

Daniel Vennemeyer, Phan Anh Duong, Meryl Ye +2

Sycophancy in language models is typically studied as excessive agreement or validation, while explicit praise and flattery have received comparatively little attention. We argue t…

cs.CY2026

Engagement-Optimized Care: When LLMs become Mental Health Infrastructure

Briana Vecchione, Meryl Ye, Livia Garofalo +1

General-purpose LLMs are increasingly functioning as mental health infrastructure due to gaps in care left by provider shortages, inadequate insurance coverage, social isolation, a…

cs.HC2026

The Capacity to Care: Designing Social Technology for Sustained Engagement With Societal Challenges

JaeWon Kim, Lindsay Popowski, Louisa Conwill +12

People care about climate change, injustice, and humanitarian crises. The challenge is not apathy but capacity: sustained engagement with large-scale problems is psychologically co…

cs.AI2026

What Counts as AI Sycophancy? A Taxonomy and Expert Survey of a Fragmented Construct

Meryl Ye, Lujain Ibrahim, Jessica Y. Bo +5

AI sycophancy has become a prominent concern in large language model (LLM) research. Yet the term lacks a consistent definition and has been applied to behaviors ranging from agree…

cs.HC2026

Supporting Informed Self-Disclosure: Design Recommendations for Presenting AI-Estimates of Privacy Risks to Users

Isadora Krsek, Meryl Ye, Wei Xu +3

People candidly discuss sensitive topics online under the perceived safety of anonymity; yet, for many, this perceived safety is tenuous, as miscalibrated risk perceptions can lead…