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
- 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)
- PDF:
- https://preview.aclanthology.org/autopr/N19-1420.pdf
- Code
- wabyking/qnn
- Data
- WikiQA