CNM: An Interpretable Complex-valued Network for Matching

Qiuchi Li, Benyou Wang, Massimo Melucci


Abstract
This paper seeks to model human language by the mathematical framework of quantum physics. With the well-designed mathematical formulations in quantum physics, this framework unifies different linguistic units in a single complex-valued vector space, e.g. words as particles in quantum states and sentences as mixed systems. A complex-valued network is built to implement this framework for semantic matching. With well-constrained complex-valued components, the network admits interpretations to explicit physical meanings. The proposed complex-valued network for matching (CNM) achieves comparable performances to strong CNN and RNN baselines on two benchmarking question answering (QA) datasets.
Anthology ID:
N19-1420
Volume:
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Jill Burstein, Christy Doran, Thamar Solorio
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4139–4148
Language:
URL:
https://aclanthology.org/N19-1420
DOI:
10.18653/v1/N19-1420
Award:
 Best Explainable NLP Paper
Bibkey:
Cite (ACL):
Qiuchi Li, Benyou Wang, and Massimo Melucci. 2019. CNM: An Interpretable Complex-valued Network for Matching. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 4139–4148, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
CNM: An Interpretable Complex-valued Network for Matching (Li et al., NAACL 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/improve-issue-templates/N19-1420.pdf
Video:
 https://vimeo.com/365160781
Code
 wabyking/qnn
Data
WikiQA