224 citations
- Microsoft (Canada)CA10 papers
- Microsoft (United States)US10 papers
- McGill UniversityCA4 papers
- Carnegie Mellon UniversityUS3 papers
- Georgia Institute of TechnologyUS3 papers
- Microsoft Research (United Kingdom)GB3 papers
- Université de MontréalCA3 papers
- Allen Institute for Artificial IntelligenceUS2 papers
- Boise State UniversityUS2 papers
- Centre Universitaire de MilaDZ2 papers
- Microsoft Research New York City (United States)2 papers
- Polytechnique MontréalCA2 papers
Showing 2025Show all
3 papers · 1 filter
cs.HC2025★ 22 cited
A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies
Alicia DeVrio, Myra Cheng, Lisa Egede +2
Recent attention to anthropomorphism -- the attribution of human-like qualities to non-human objects or entities -- of language technologies like LLMs has sparked renewed discussio…
cs.HC2025★ 52 cited
Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao +2
Large language models (LLMs) can produce erroneous responses that sound fluent and convincing, raising the risk that users will rely on these responses as if they were correct. Mit…
cs.HC2025★ 32 cited
As Confidence Aligns: Exploring the Effect of AI Confidence on Human Self-confidence in Human-AI Decision Making
Jingshu Li, Yitian Yang, Q. Vera Liao +2
Complementary collaboration between humans and AI is essential for human-AI decision making. One feasible approach to achieving it involves accounting for the calibrated confidence…