most cited"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Situated Practice Systems: A Computational System for Supporting the Coaching and Practice of Regulation Skills for Innovation Work

Kapil Garg, Darren Gergle, Haoqi Zhang

Students are increasingly expected to prepare for open-ended innovation work, which requires well-developed cognitive, metacognitive, and emotional regulation skills. College learn…

cs.HC20262 cited

"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models

Kapil Garg, Xinru Tang, Jimin Heo +4

Vision-Language Models (VLMs) are increasingly used by blind and low-vision (BLV) people to identify and understand products in their everyday lives, such as food, personal care it…

cs.SE2026

Linguistic Similarity Within Centralized FLOSS Development

Matthew Gaughan, Aaron Shaw, Darren Gergle

When free/libre and open source software (FLOSS) stewards centralize project development, they potentially undermine project sustainability and impact how contributors talk to each…

cs.HC2026

The Agony of Opacity: Foundations for Reflective Interpretability in AI-Mediated Mental Health Support

Sachin R. Pendse, Darren Gergle, Rachel Kornfield +6

Throughout history, a prevailing paradigm in mental healthcare has been one in which distressed people may receive treatment with little understanding around how their experience i…

cs.CY2025

When Testing AI Tests Us: Safeguarding Mental Health on the Digital Frontlines

Sachin R. Pendse, Darren Gergle, Rachel Kornfield +6

Red-teaming is a core part of the infrastructure that ensures that AI models do not produce harmful content. Unlike past technologies, the black box nature of generative AI systems…