Towards Cognitively More Plausible Models

Author:

Beinborn Lisa,Hollenstein Nora

Publisher

Springer International Publishing

Reference26 articles.

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2. Ruiqi Zhong, Dhruba Ghosh, Dan Klein, and Jacob Steinhardt. Are larger pretrained language models uniformly better? comparing performance at the instance level. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 3813–3827, Online, August 2021. Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.findings-acl.334. https://aclanthology.org/2021.findings-acl.334.

3. Urja Khurana, Eric Nalisnick, and Antske Fokkens. How emotionally stable is ALBERT? testing robustness with stochastic weight averaging on a sentiment analysis task. In Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems, pages 16–31, Punta Cana, Dominican Republic, November 2021. Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.eval4nlp-1.3. https://aclanthology.org/2021.eval4nlp-1.3

4. Valerio Basile, Michael Fell, Tommaso Fornaciari, Dirk Hovy, Silviu Paun, Barbara Plank, Massimo Poesio, and Alexandra Uma. We need to consider disagreement in evaluation. In Proceedings of the 1st Workshop on Benchmarking: Past, Present and Future, pages 15–21, Online, August 2021. Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.bppf-1.3. https://aclanthology.org/2021.bppf-1.3

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