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• ADCanvas: Accessible and Conversational Audio Description Authoring for Blind and Low Vision Creators

  Franklin Mingzhe Li, Michael Xieyang Liu, Cynthia L Bennett, Shaun K. Kane · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Li and colleagues tackle a rarely examined corner of accessibility: the fact that the tools used to produce Audio Description (AD) are themselves largely inaccessible to the blind and low-vision (BLV) creators who are often its most skilled practitioners. Professional AD…

  audio description · blind and low vision · conversational agent · multimodal LLM · visual question answering

• 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

• Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users

  Farnaz Zamiri Zeraati, Yang Cao, Yuehan Qiao, Hal Daumé III, Hernisa Kacorri · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper investigates how blind users can exert control over responses generated by conversational visual question answering (VQA) systems built on vision-language models. While prompting and steering techniques are well established in general-purpose generative AI,…

  blind users · generative AI · visual question answering · VQA · personalization

• ViDscribe: Multimodal AI for Customizing Audio Description and Question Answering in Online Videos

  Maryam S Cheema, Sina Elahimanesh, Pooyan Fazli, Hasti Seifi · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA '26)

  Cheema and colleagues (Arizona State University and Saarland University) present ViDscribe, a web platform that layers AI-generated audio description (AD) and conversational visual question answering (VQA) on top of arbitrary YouTube videos for blind and low vision (BLV)…

  video accessibility · audio description · blind and low vision · multimodal large language models · visual question answering

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