How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People
Ricardo E. Gonzalez Penuela, Crescentia Jung, Sharon Lin, Ruiying Hu, Shiri Azenkot · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)
This CHI 2026 paper reports a two-week diary study with 20 Blind and Low Vision (BLV) participants (ages 19–75, 11 female/9 male, 13 blind/7 low vision) investigating how multimodal large language models (MLLMs) support real-world access to visual information. The authors built…
AI · accessibility · multimodal large language models · MLLM · visual question answering