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Publications by Schick, Timo

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Number of items: 14.

Journal article

Schick, Timo; Schuetze, Hinrich (2020): Rare Words: A Major Problem for Contextualized Embeddings and How to Fix it by Attentive Mimicking. In: Thirty-Fourth Aaai Conference on Artificial Intelligence, the Thirty-Second Innovative Applications of Artificial Intelligence Conference and the Tenth Aaai Symposium on Educational Advances in Artificial Intelligence, Vol. 34: pp. 8766-8774

Schick, Timo; Schuetze, Hinrich (2020): BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance. In: 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020): pp. 3996-4007

Schick, Timo; Schuetze, Hinrich (2019): Learning Semantic Representations for Novel Words: Leveraging Both Form and Context. In: Thirty-Third Aaai Conference on Artificial Intelligence / Thirty-First Innovative Applications of Artificial Intelligence Conference / Ninth Aaai Symposium on Educational Advances in Artificial Intelligence: pp. 6965-6973

Paper

Schick, Timo; Udupa, Sahana ORCID: 0000-0003-3647-9570; Schütze, Hinrich (2021): Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in NLP. arXiv

Conference or Workshop Item

Senel, Lütfi Kerem; Schick, Timo; Schütze, Hinrich (May 2022): CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition Alignment. 60th Annual Meeting of the Association for Computational Linguistics, May 2022, Dublin, Ireland. [PDF, 290kB]

Schick, Timo; Schütze, Hinrich (November 2021): Few-Shot Text Generation with Natural Language Instructions. 2021 Conference on Empirical Methods in Natural Language Processing, November 7–11, 2021, Online and Punta Cana, Dominican Republic. [PDF, 504kB]

Schick, Timo; Schütze, Hinrich (November 2021): Generating Datasets with Pretrained Language Models. 2021 Conference on Empirical Methods in Natural Language Processing, November 7-11, 2021, Online and Punta Cana, Dominican Republic. [PDF, 431kB]

Schick, Timo; Schütze, Hinrich (June 2021): It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, June 2021, Online. [PDF, 475kB]

Schick, Timo; Schütze, Hinrich (April 2021): Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference. 16th Conference of the European Chapter of the Association for Computational Linguistics, April 19-23, 2021, Online. [PDF, 493kB]

Schick, Timo; Schmid, Helmut; Schütze, Hinrich (December 2020): Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification. The 28th International Conference on Computational Linguistics, 8. - 11. Dezember 2020, Online. [PDF, 275kB]

Schick, Timo; Schütze, Hinrich (6. July 2020): BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance. The 58th Annual Meeting of the Association for Computational Linguistics, July 6 – 8, 2020, Seattle, USA. [PDF, 399kB]

Schick, Timo; Schütze, Hinrich (June 2019): Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts. 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2. - 7. June 2019, Minneapolis, USA. [PDF, 304kB]

Schick, Timo; Schütze, Hinrich (April 2019): Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), February 7-12, 2020, New York, USA. [PDF, 372kB]

Schick, Timo; Schütze, Hinrich (January 2019): Learning Semantic Representations for Novel Words: Leveraging Both Form and Context. Thirty-Third AAAI Conference on Artificial Intelligence; AAAI-2019, 27. January – 01. February 2019, Honolulu, Hawaii, USA. [PDF, 165kB]

This list was generated on Sun May 29 10:21:42 2022 CEST.