Tensor Product Decomposition Networks: Uncovering Representations of Structure Learned by Neural Networks
- Anthology ID:
- 2020.scil-1.34
- Volume:
- Proceedings of the Society for Computation in Linguistics 2020
- Month:
- January
- Year:
- 2020
- Address:
- New York, New York
- Editors:
- Allyson Ettinger, Gaja Jarosz, Joe Pater
- Venue:
- SCiL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 277–278
- Language:
- URL:
- https://aclanthology.org/2020.scil-1.34
- DOI:
- Cite (ACL):
- R. Thomas McCoy, Tal Linzen, Ewan Dunbar, and Paul Smolensky. 2020. Tensor Product Decomposition Networks: Uncovering Representations of Structure Learned by Neural Networks. In Proceedings of the Society for Computation in Linguistics 2020, pages 277–278, New York, New York. Association for Computational Linguistics.
- Cite (Informal):
- Tensor Product Decomposition Networks: Uncovering Representations of Structure Learned by Neural Networks (McCoy et al., SCiL 2020)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/2020.scil-1.34.pdf