Literature Reviews
Reviewed research papers, articles, and publications relevant to digital accessibility.
8 results found tagged prompt engineering.
-
Making Charts Speak: LLM-Based Conversational Chart Question Answering for Blind and Low-Vision Users
Das, Tarun, and Mueller present GraphWhisper, a conversational system that lets blind and low-vision (BLV) users explore chart images (JPEG, PNG) through natural-language questions, without requiring the chart data to be pre-structured in formats lik…
-
Interface Support for Evaluating Disability Bias in AI-Generated Images
Mack and colleagues investigate whether interface-level interventions can help users of generative text-to-image (T2I) tools recognise and avoid disability stereotypes in AI-generated images. The authors frame the work around a gap in AI safety: whil…
-
Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users
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 gen…
-
Towards Testing the Accessibility of Dynamic Visual Changes in Android Mobile GUI with Multi-Modal LLMs
This paper addresses a long-standing gap in mobile accessibility testing: dynamic visual changes in Android GUIs that communicate task status or feedback to sighted users but are invisible to blind users of screen readers such as TalkBack. Examples i…
-
When LLM-Generated Code Perpetuates User Interface Accessibility Barriers, How Can We Break the Cycle?
This paper evaluates the ability of large language models (LLMs) to generate accessible web user interfaces, comparing ChatGPT (GPT-4-turbo) and Claude (3.5 Haiku) across two prompting strategies: accessibility-agnostic prompts ("Design the homepage …
-
SoundNarratives: Rich Auditory Scene Descriptions to Support Deaf and Hard of Hearing People
This paper introduces SoundNarratives, a real-time system that generates rich, contextual auditory scene descriptions tailored to deaf and hard of hearing (DHH) users. Existing sound recognition technologies typically classify sounds into predefined …
-
AccessGuru: Leveraging LLMs to Detect and Correct Web Accessibility Violations in HTML Code
This paper introduces AccessGuru, a novel method that combines traditional automated accessibility testing tools with large language models (LLMs) to both detect and correct web accessibility violations in HTML code. The work addresses a persistent g…
-
MAIDR Meets AI: Exploring Multimodal LLM-Based Data Visualization Interpretation by and with Blind and Low-Vision Users
This paper investigates how blind and low-vision (BLV) users interact with large language models to interpret data visualizations, building on the authors' previously developed MAIDR (Multimodal Access and Interactive Data Representation) framework. …