Large Language Models as Zero-Shot Human Models for Human-Robot Interaction

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B. D. Ziebart, N. Ratliff, G. Gallagher, C. Mertz, K. Peterson, J. A. Bagnell, M. Hebert, A. K. Dey, and S. Srinivasa, “Planning-based prediction for pedestrians,” in 2009 IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems . IEEE, 2009, pp. 3931–3936
2009
Earlier work this paper cites.
J. Zhang, T. Hedden, and A. Chia, “Perspective-taking and depth of theory-of-mind reasoning in sequential-move games,” Cognitive science , vol. 36, no. 3, pp. 560–573, 2012
2012
Earlier work this paper cites.
C. L. Baker and J. B. Tenenbaum, “Modeling human plan recognition using bayesian theory of mind,” Plan, activity, and intent recognition: Theory and practice , vol. 7, pp. 177–204, 2014
2014
Earlier work this paper cites.
C. M. Heyes and C. D. Frith, “The cultural evolution of mind reading,” Science , vol. 344, no. 6190, p. 1243091, 2014
2014
Earlier work this paper cites.
D. Sadigh, S. Sastry, S. A. Seshia, and A. D. Dragan, “Planning for autonomous cars that leverage effects on human actions.” in Robotics: Science and systems , vol. 2. Ann Arbor, MI, USA, 2016, pp. 1–9
2016
Earlier work this paper cites.
A. Thomaz, G. Hoffman, M. Cakmak et al. , “Computational human-robot interaction,” Foundations and Trends® in Robotics , vol. 4, no. 2-3, pp. 105–223, 2016
2016
Earlier work this paper cites.
C. L. Baker, J. Jara-Ettinger, R. Saxe, and J. B. Tenenbaum, “Rational quantitative attribution of beliefs, desires and percepts in human mentalizing,” Nature Human Behaviour , vol. 1, no. 4, p. 0064, 2017
2017
Earlier work this paper cites.
M. Chen, S. Nikolaidis, H. Soh, D. Hsu, and S. Srinivasa, “Planning with trust for human-robot collaboration,” in Proceedings of the 2018 ACM/IEEE Intl. Conf. on human-robot interaction , 2018, pp. 307–315
2018
Earlier work this paper cites.
E. Schmerling, K. Leung, W. Vollprecht, and M. Pavone, “Multimodal probabilistic model-based planning for human-robot interaction,” in 2018 IEEE Intl. Conf. on Robotics and Automation (ICRA) . IEEE, 2018, pp. 3399–3406
2018
Earlier work this paper cites.
H. Soh, P. Shu, M. Chen, and D. Hsu, “The transfer of human trust in robot capabilities across tasks.” in R:SS , 2018
2018
Earlier work this paper cites.
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “Bert: Pre-training of deep bidirectional transformers for language understanding,” arXiv preprint arXiv:1810.04805 , 2018
Original
2018
Earlier work this paper cites.
R. Choudhury, G. Swamy, D. Hadfield-Menell, and A. D. Dragan, “On the utility of model learning in hri,” in 2019 14th ACM/IEEE Intl. Conf. on Human-Robot Interaction (HRI) . IEEE, 2019, pp. 317–325
2019
Earlier work this paper cites.

Similar

O. Nocentini, L. Fiorini, G. Acerbi, A. Sorrentino, G. Mancioppi, and F. Cavallo, “A survey of behavioral models for social robots,” Robotics , vol. 8, no. 3, p. 54, 2019
2019
Cited alongside, same era.
J. J. Lee, F. Sha, and C. Breazeal, “A bayesian theory of mind approach to nonverbal communication,” in 2019 14th ACM/IEEE Intl. Conf. on Human-Robot Interaction (HRI) . IEEE, 2019, pp. 487–496
2019
Cited alongside, same era.
M. Sap, H. Rashkin, D. Chen, R. LeBras, and Y. Choi, “Socialiqa: Commonsense reasoning about social interactions,” arXiv preprint arXiv:1904.09728 , 2019
Original
2019
Cited alongside, same era.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell et al. , “Language models are few-shot learners,” Advances in neural information processing systems , vol. 33, pp. 1877–1901, 2020
2020
Cited alongside, same era.

Then

A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann et al. , “Palm: Scaling language modeling with pathways,” arXiv preprint arXiv:2204.02311 , 2022
Original
2022
Later among the works it cites.
G. Aher, R. I. Arriaga, and A. T. Kalai, “Using large language models to simulate multiple humans,” arXiv preprint arXiv:2208.10264 , 2022
Original
2022
Later among the works it cites.
M. Ahn, A. Brohan, N. Brown, Y. Chebotar, O. Cortes, B. David, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog et al. , “Do as i can, not as i say: Grounding language in robotic affordances,” arXiv preprint arXiv:2204.01691 , 2022
Original
2022
Later among the works it cites.
J. Tjomsland, S. Kalkan, and H. Gunes, “Mind your manners! a dataset and a continual learning approach for assessing social appropriateness of robot actions,” Frontiers in Robotics and AI , vol. 9, p. 4, 2022
2022
Later among the works it cites.

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Large Language Models as Zero-Shot Human Models for Human-Robot Interaction · Around

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B. D. Ziebart, N. Ratliff, G. Gallagher, C. Mertz, K. Peterson, J. A. Bagnell, M. Hebert, A. K. Dey, and S. Srinivasa, “Planning-based prediction for pedestrians,” in 2009 IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems . IEEE, 2009, pp. 3931–3936
2009
Earlier work this paper cites.
J. Zhang, T. Hedden, and A. Chia, “Perspective-taking and depth of theory-of-mind reasoning in sequential-move games,” Cognitive science , vol. 36, no. 3, pp. 560–573, 2012
2012
Earlier work this paper cites.
C. L. Baker and J. B. Tenenbaum, “Modeling human plan recognition using bayesian theory of mind,” Plan, activity, and intent recognition: Theory and practice , vol. 7, pp. 177–204, 2014
2014
Earlier work this paper cites.
C. M. Heyes and C. D. Frith, “The cultural evolution of mind reading,” Science , vol. 344, no. 6190, p. 1243091, 2014
2014
Earlier work this paper cites.
D. Sadigh, S. Sastry, S. A. Seshia, and A. D. Dragan, “Planning for autonomous cars that leverage effects on human actions.” in Robotics: Science and systems , vol. 2. Ann Arbor, MI, USA, 2016, pp. 1–9
2016
Earlier work this paper cites.
A. Thomaz, G. Hoffman, M. Cakmak et al. , “Computational human-robot interaction,” Foundations and Trends® in Robotics , vol. 4, no. 2-3, pp. 105–223, 2016
2016
Earlier work this paper cites.
C. L. Baker, J. Jara-Ettinger, R. Saxe, and J. B. Tenenbaum, “Rational quantitative attribution of beliefs, desires and percepts in human mentalizing,” Nature Human Behaviour , vol. 1, no. 4, p. 0064, 2017
2017
Earlier work this paper cites.
M. Chen, S. Nikolaidis, H. Soh, D. Hsu, and S. Srinivasa, “Planning with trust for human-robot collaboration,” in Proceedings of the 2018 ACM/IEEE Intl. Conf. on human-robot interaction , 2018, pp. 307–315
2018
Earlier work this paper cites.
E. Schmerling, K. Leung, W. Vollprecht, and M. Pavone, “Multimodal probabilistic model-based planning for human-robot interaction,” in 2018 IEEE Intl. Conf. on Robotics and Automation (ICRA) . IEEE, 2018, pp. 3399–3406
2018
Earlier work this paper cites.
H. Soh, P. Shu, M. Chen, and D. Hsu, “The transfer of human trust in robot capabilities across tasks.” in R:SS , 2018
2018
Earlier work this paper cites.
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “Bert: Pre-training of deep bidirectional transformers for language understanding,” arXiv preprint arXiv:1810.04805 , 2018
Original
2018
Earlier work this paper cites.
R. Choudhury, G. Swamy, D. Hadfield-Menell, and A. D. Dragan, “On the utility of model learning in hri,” in 2019 14th ACM/IEEE Intl. Conf. on Human-Robot Interaction (HRI) . IEEE, 2019, pp. 317–325
2019
Earlier work this paper cites.

Similar

O. Nocentini, L. Fiorini, G. Acerbi, A. Sorrentino, G. Mancioppi, and F. Cavallo, “A survey of behavioral models for social robots,” Robotics , vol. 8, no. 3, p. 54, 2019
2019
Cited alongside, same era.
J. J. Lee, F. Sha, and C. Breazeal, “A bayesian theory of mind approach to nonverbal communication,” in 2019 14th ACM/IEEE Intl. Conf. on Human-Robot Interaction (HRI) . IEEE, 2019, pp. 487–496
2019
Cited alongside, same era.
M. Sap, H. Rashkin, D. Chen, R. LeBras, and Y. Choi, “Socialiqa: Commonsense reasoning about social interactions,” arXiv preprint arXiv:1904.09728 , 2019
Original
2019
Cited alongside, same era.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell et al. , “Language models are few-shot learners,” Advances in neural information processing systems , vol. 33, pp. 1877–1901, 2020
2020
Cited alongside, same era.

Then

A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann et al. , “Palm: Scaling language modeling with pathways,” arXiv preprint arXiv:2204.02311 , 2022
Original
2022
Later among the works it cites.
G. Aher, R. I. Arriaga, and A. T. Kalai, “Using large language models to simulate multiple humans,” arXiv preprint arXiv:2208.10264 , 2022
Original
2022
Later among the works it cites.
M. Ahn, A. Brohan, N. Brown, Y. Chebotar, O. Cortes, B. David, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog et al. , “Do as i can, not as i say: Grounding language in robotic affordances,” arXiv preprint arXiv:2204.01691 , 2022
Original
2022
Later among the works it cites.
J. Tjomsland, S. Kalkan, and H. Gunes, “Mind your manners! a dataset and a continual learning approach for assessing social appropriateness of robot actions,” Frontiers in Robotics and AI , vol. 9, p. 4, 2022
2022
Later among the works it cites.

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