ML Anthology

Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract)

Annika Heuser, Polina Tsvilodub
AAAI 2021 pp. 15799-15800
doi:10.1609/AAAI.V35I18.17896 /aaai/2021/heuser2021aaai-comparing/

Abstract

Given recurring interest in structured representations in computational cognitive models, we extend a Bayesian scoring procedure for comparing symbolic models of language grammar. We conduct a case-study of modeling syntactic principles in German, providing preliminary results consistent with linguistic theory. We also note that dataset and part-of-speech (POS) tagger quality should not be taken for granted.

PDF AAAI Semantic Scholar

Cite

Text

Heuser and Tsvilodub. "Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I18.17896

Markdown

[Heuser and Tsvilodub. "Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/heuser2021aaai-comparing/) doi:10.1609/AAAI.V35I18.17896

BibTeX

@inproceedings{heuser2021aaai-comparing,
  title     = {{Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract)}},
  author    = {Heuser, Annika and Tsvilodub, Polina},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {15799-15800},
  doi       = {10.1609/AAAI.V35I18.17896},
  url       = {https://mlanthology.org/aaai/2021/heuser2021aaai-comparing/}
}