![[höher]](/style/images/multi_up.png)
Eine Ebene höherGruppiert nach:
Dokumententyp
| Veröffentlichungsdatum
Anzahl der Publikationen: 17
Zeitschriftenartikel
Schick, Timo und Schütze, Hinrich
(2022):
True Few-Shot Learning with Prompts—A Real-World Perspective.
In: Transactions of the Association for Computational Linguistics, Bd. 10: S. 716-731
[PDF, 547kB]
Schick, Timo; Udupa, Sahana 
ORCID: https://orcid.org/0000-0003-3647-9570 und Schütze, Hinrich
(17. Dezember 2021):
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP.
In: Transactions of the Association for Computational Linguistics, Bd. 9: S. 1408-1424
[PDF, 411kB]
ORCID: https://orcid.org/0000-0003-3647-9570 und Schütze, Hinrich
(17. Dezember 2021):
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP.
In: Transactions of the Association for Computational Linguistics, Bd. 9: S. 1408-1424
[PDF, 411kB]
Schick, Timo; Udupa, Sahana und Schütze, Hinrich
(2021):
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP.
In: Transactions of the Association for Computational Linguistics, Bd. 9: S. 1408-1424
Schick, Timo und 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): S. 3996-4007
Schick, Timo und 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, Bd. 34: S. 8766-8774
Schick, Timo und 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: S. 6965-6973
Paper
Schick, Timo; Udupa, Sahana ORCID: https://orcid.org/0000-0003-3647-9570 und Schütze, Hinrich
(2021):
Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in NLP.
arXiv
ORCID: https://orcid.org/0000-0003-3647-9570 und Schütze, Hinrich
(2021):
Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in NLP.
arXiv
Konferenzbeitrag
Senel, Lütfi Kerem; Schick, Timo und Schütze, Hinrich
(Mai 2022):
CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition Alignment.
60th Annual Meeting of the Association for Computational Linguistics, Dublin, Ireland, May 2022.
Muresan, Smaranda; Nakov, Preslav und Villavicencio, Aline (Hrsg.):
In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers),
Stroudsburg, PA: Association for Computational Linguistics. S. 815-824
[PDF, 290kB]
Schick, Timo und Schütze, Hinrich
(November 2021):
Few-Shot Text Generation with Natural Language Instructions.
2021 Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, November 7–11, 2021.
Moens, Marie-Francine; Huang, Xuanjing; Specia, Lucia und Yih, Scott Wen-tau (Hrsg.):
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing,
Stroudsburg, PA: Association for Computational Linguistics. S. 390-402
[PDF, 504kB]
Schick, Timo und Schütze, Hinrich
(November 2021):
Generating Datasets with Pretrained Language Models.
2021 Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, November 7-11, 2021.
Moens, Marie-Francine; Specia, Lucia; Huang, Xuanjing und Yih, Scott Wen-tau (Hrsg.):
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing,
Stroudsburg, PA: Association for Computational Linguistics. S. 6943-6951
[PDF, 431kB]
Schick, Timo und Schütze, Hinrich
(Juni 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, Online, June 2021.
Toutanova, Kristina (Hrsg.):
In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies,
Stroudsburg, PA: Association for Computational Linguistics. S. 2339-2352
[PDF, 475kB]
Schick, Timo und 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, Online, April 19-23, 2021.
Merlo, Paola; Tiedemann, Jörg und Tsarfaty, Reut (Hrsg.):
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume,
Stroudsburg, PA: Association for Computational Linguistics. S. 255-269
[PDF, 493kB]
Schick, Timo; Schmid, Helmut und Schütze, Hinrich
(Dezember 2020):
Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification.
The 28th International Conference on Computational Linguistics, Online, 8. - 11. Dezember 2020.
[PDF, 275kB]
Schick, Timo und Schütze, Hinrich
(6. Juli 2020):
BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance.
The 58th Annual Meeting of the Association for Computational Linguistics, Seattle, USA, July 6 – 8, 2020.
[PDF, 399kB]
Schick, Timo und Schütze, Hinrich
(Juni 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, Minneapolis, USA, 2. - 7. June 2019.
Association for Computational Linguistics.
[PDF, 304kB]
Schick, Timo und 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), New York, USA, February 7-12, 2020.
[PDF, 372kB]
Schick, Timo und Schütze, Hinrich
(Januar 2019):
Learning Semantic Representations for Novel Words:
Leveraging Both Form and Context.
Thirty-Third AAAI Conference on Artificial Intelligence; AAAI-2019, Honolulu, Hawaii, USA, 27. January – 01. February 2019.
[PDF, 165kB]