Switching Contexts: Transportability Measures for NLP

Guy Marshall, Mokanarangan Thayaparan, Philip Osborne, André Freitas


Abstract
This paper explores the topic of transportability, as a sub-area of generalisability. By proposing the utilisation of metrics based on well-established statistics, we are able to estimate the change in performance of NLP models in new contexts. Defining a new measure for transportability may allow for better estimation of NLP system performance in new domains, and is crucial when assessing the performance of NLP systems in new tasks and domains. Through several instances of increasing complexity, we demonstrate how lightweight domain similarity measures can be used as estimators for the transportability in NLP applications. The proposed transportability measures are evaluated in the context of Named Entity Recognition and Natural Language Inference tasks.
Anthology ID:
2021.iwcs-1.1
Volume:
Proceedings of the 14th International Conference on Computational Semantics (IWCS)
Month:
June
Year:
2021
Address:
Groningen, The Netherlands (online)
Venue:
IWCS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–10
Language:
URL:
https://aclanthology.org/2021.iwcs-1.1
DOI:
Bibkey:
Cite (ACL):
Guy Marshall, Mokanarangan Thayaparan, Philip Osborne, and André Freitas. 2021. Switching Contexts: Transportability Measures for NLP. In Proceedings of the 14th International Conference on Computational Semantics (IWCS), pages 1–10, Groningen, The Netherlands (online). Association for Computational Linguistics.
Cite (Informal):
Switching Contexts: Transportability Measures for NLP (Marshall et al., IWCS 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.iwcs-1.1.pdf
Code
 ai-systems/transportability
Data
MultiNLISNLI