Use Defines Possibilities: Reasoning about Object Function to Interpret and Execute Robot Instructions

Mollie Shichman, Claire Bonial, Austin Blodgett, Taylor Hudson, Francis Ferraro, Rachel Rudinger

Abstract
Language models have shown great promise in common-sense related tasks. However, it remains unseen how they would perform in the context of physically situated human-robot interactions, particularly in disaster-relief sce- narios. In this paper, we develop a language model evaluation dataset with more than 800 cloze sentences, written to probe for the func- tion of over 200 objects. The sentences are divided into two tasks: an “easy” task where the language model has to choose between vo- cabulary with different functions (Task 1), and a “challenge” where it has to choose between vocabulary with the same function, yet only one vocabulary item is appropriate given real world constraints on functionality (Task 2). Dis- tilBERT performs with about 80% accuracy for both tasks. To investigate how annotator variability affected those results, we developed a follow-on experiment where we compared our original results with wrong answers chosen based on embedding vector distances. Those results showed increased precision across docu- ments but a 15% decrease in accuracy. We con- clude that language models do have a strong knowledge basis for object reasoning, but will require creative fine-tuning strategies in order to be successfully deployed.
Anthology ID:
2023.iwcs-1.30
Volume:
Proceedings of the 15th International Conference on Computational Semantics
Month:
June
Year:
2023
Address:
Nancy, France
Editors:
Maxime Amblard, Ellen Breitholtz
Venue:
IWCS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
284–292
Language:
URL:
https://aclanthology.org/2023.iwcs-1.30
DOI:
Bibkey:
Cite (ACL):
Mollie Shichman, Claire Bonial, Austin Blodgett, Taylor Hudson, Francis Ferraro, and Rachel Rudinger. 2023. Use Defines Possibilities: Reasoning about Object Function to Interpret and Execute Robot Instructions. In Proceedings of the 15th International Conference on Computational Semantics, pages 284–292, Nancy, France. Association for Computational Linguistics.
Cite (Informal):
Use Defines Possibilities: Reasoning about Object Function to Interpret and Execute Robot Instructions (Shichman et al., IWCS 2023)
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