Toward Compositional Behavior in Neural Models: A Survey of Current Views
Kate McCurdy, Paul Soulos, Paul Smolensky, Roland Fernandez, Jianfeng Gao
Abstract
Compositionality is a core property of natural language, and compositional behavior (CB) is a crucial goal for modern NLP systems. The research literature, however, includes conflicting perspectives on how CB should be defined, evaluated, and achieved. We propose a conceptual framework to address these questions and survey researchers active in this area.We find consensus on several key points. Researchers broadly accept our proposed definition of CB, agree that it is not solved by current models, and doubt that scale alone will achieve the target behavior. In other areas, we find the field is split on how to move forward, identifying diverse opportunities for future research.
BibTeX
@inproceedings{mccurdy-etal-2024-toward,
title = "Toward Compositional Behavior in Neural Models: A Survey of Current Views",
author = "McCurdy, Kate and
Soulos, Paul and
Smolensky, Paul and
Fernandez, Roland and
Gao, Jianfeng",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.524/",
doi = "10.18653/v1/2024.emnlp-main.524",
pages = "9323--9339"
}