Trust in Language Grounding: a new AI challenge for human-robot teams
September 05, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
David M. Bossens, Christine Evers
arXiv ID
2209.02066
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LG,
cs.RO
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The challenge of language grounding is to fully understand natural language by grounding language in real-world referents. While AI techniques are available, the widespread adoption and effectiveness of such technologies for human-robot teams relies critically on user trust. This survey provides three contributions relating to the newly emerging field of trust in language grounding, including a) an overview of language grounding research in terms of AI technologies, data sets, and user interfaces; b) six hypothesised trust factors relevant to language grounding, which are tested empirically on a human-robot cleaning team; and c) future research directions for trust in language grounding.
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