Referring to Screen Texts with Voice Assistants
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Abstract (arXiv)
Voice assistants help users make phone calls, send messages, create events, navigate, and do a lot more. However, assistants have limited capacity to understand their users' context. In this work, we aim to take a step in this direction. Our work dives into a new experience for users to refer to phone numbers, addresses, email addresses, URLs, and dates on their phone screens. Our focus lies in reference understanding, which becomes particularly interesting when multiple similar texts are present on screen, similar to visual grounding. We collect a dataset and propose a lightweight general-purpose model for this novel experience. Due to the high cost of consuming pixels directly, our system is designed to rely on the extracted text from the UI. Our model is modular, thus offering flexibility, improved interpretability, and efficient runtime memory utilization.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 35 references that are in the map. First posted on arXiv 10 Jun 2023.
Builds on
14 of 35 references.
References · 14
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- 2019Scene Text Visual Question Answeringcited by 331
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- 2022ScreenQA: Large-Scale Question-Answer Pairs over Mobile App Screenshotscited by 66
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2 more
Built on by
Citing papers per year: 2023: 1; 2024: 1.
2 papers.
- 2024ReALM: Reference Resolution As Language Modelingcited by 7
- 2023MARRS: Multimodal Reference Resolution Systemcited by 1
- 2024ReALM: Reference Resolution As Language Modeling29 Mar 2024
- 2023MARRS: Multimodal Reference Resolution System3 Nov 2023