at Google ScholarTitle data
Dang, Hai ; Lafreniere, Ben ; Grossman, Tovi ; Todi, Kashyap ; Li, Michelle:
Authoring LLM-Based Assistance for Real-World Contexts and Tasks.
In:
Proceedings of the 30th International Conference on Intelligent User Interfaces. -
New York, NY
: Association for Computing Machinery
,
2025
. - pp. 211-230
ISBN 9798400713064
DOI: https://doi.org/10.1145/3708359.3712164
Abstract in another language
Advances in AI hold the possibility of assisting users with highly varied and individual needs, but the breadth of assistance that these systems could provide creates a challenge for how users specify their goals to the system. To support the authoring of AI assistance for real-world tasks, we propose the concept of Contextually-Driven Prompts (CDPs) that define how an AI assistant should respond to real-world context. We implemented a prototype system for authoring and executing CDPs, which provides suggestions to assist users with finding the right level of assistance for their goal. We also conducted a user study (N=10) to investigate how participants express and refine their goals for real-world tasks. Results revealed a number of strategies for initiating and refining CDPs with suggestions, and implications for the design of future authoring interfaces.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| Keywords: | virtual assistants; voice-based interaction; large language model; vision language model; generative AI |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IX |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 18 Mar 2026 07:53 |
| Last Modified: | 18 Mar 2026 12:03 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/96610 |