Understanding Large-Language Model (LLM)-powered Human-Robot Interaction-Reference-Cited by-同舟云学术

Understanding Large-Language Model (LLM)-powered Human-Robot Interaction

Published:2024-03-11 Issue: Volume:2799 Page:371-380
ISSN:
Container-title:Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
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Author:

Kim Callie Y.¹^ORCID,Lee Christine P.¹^ORCID,Mutlu Bilge¹^ORCID

Affiliation:

1. Department of Computer Sciences, University of Wisconsin - Madison, Madison, WI, USA

Funder

Sheldon B. and Marianne S. Lubar Professorship, an H.I. Romnes Faculty Fellowship, and a National Science Foundation award

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3610977.3634966

Reference77 articles.

1. Michael Ahn Anthony Brohan Noah Brown Yevgen Chebotar Omar Cortes Byron David Chelsea Finn Chuyuan Fu Keerthana Gopalakrishnan Karol Hausman et al. 2022. Do as i can not as i say: Grounding language in robotic affordances. arXiv preprint arXiv:2204.01691 (2022).

2. Will You Rely on a Robot to Find a Treasure?

3. The effect of presence on human-robot interaction

4. The Benefits of Interactions with Physically Present Robots over Video-Displayed Agents

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