  Mobile apps have become indispensable for accessing and participating in
various environments, especially for low-vision users. Users with visual
impairments can use screen readers to read the content of each screen and
understand the content that needs to be operated. Screen readers need to read
the hint-text attribute in the text input component to remind visually impaired
users what to fill in. Unfortunately, based on our analysis of 4,501 Android
apps with text inputs, over 0.76 of them are missing hint-text. These issues
are mostly caused by developers' lack of awareness when considering visually
impaired individuals. To overcome these challenges, we developed an LLM-based
hint-text generation model called HintDroid, which analyzes the GUI information
of input components and uses in-context learning to generate the hint-text. To
ensure the quality of hint-text generation, we further designed a
feedback-based inspection mechanism to further adjust hint-text. The automated
experiments demonstrate the high BLEU and a user study further confirms its
usefulness. HintDroid can not only help visually impaired individuals, but also
help ordinary people understand the requirements of input components. HintDroid
demo video: https://youtu.be/FWgfcctRbfI.
