Adapting Language Model Responses with Implicit Feedback for Effective Human-AI Collaboration

Authors

  • Jaelle Scheuerman U.S. Naval Research Laboratory
  • Shannon McGarry U.S. Naval Research Laboratory
  • Ciara Sibley U.S. Naval Research Laboratory
  • Noelle Brown U.S. Naval Research Laboratory

DOI:

https://doi.org/10.1609/aaaiss.v5i1.35568

Abstract

To be effective teammates with humans, is necessary for AI systems to deduce user state and context from implicitly collected feedback. In this extended abstract, we explore ways in which user activity and eyetracking systems can provide implicit feedback for the purpose of adapting the AI model to user's changing goals and needs.
AAAI Summer Symposium 2025 Proceedings Cover

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Published

2025-05-28

How to Cite

Scheuerman, J., McGarry, S., Sibley, C., & Brown, N. (2025). Adapting Language Model Responses with Implicit Feedback for Effective Human-AI Collaboration. Proceedings of the AAAI Symposium Series, 5(1), 98–99. https://doi.org/10.1609/aaaiss.v5i1.35568

Issue

Vol. 5 No. 1: Proceedings of the 2025 AAAI Spring Symposium Series

Section

Current and Future Varieties of Human-AI Collaboration