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Number of items: 6.
Journal article
Dufter, Philipp; Schmitt, Martin and Schütze, Hinrich
(September 2022):
Position Information in Transformers: An Overview.
In: Computational Linguistics, Vol. 48, No. 3: pp. 733-763
[PDF, 1MB]
Evert, Stefan; Heinrich, Philipp; Henselmann, Klaus; Rabenstein, Ulrich; Scherr, Elisabeth; Schmitt, Martin and Schröder, Lutz
(2019):
Combining Machine Learning and Semantic Features in the Classification of Corporate Disclosures.
In: Journal of Logic Language and Information, Vol. 28, No. 2: pp. 309-330
Schmitt, Martin and Schuetze, Hinrich
(2019):
SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference.
In: 57Th Annual Meeting of the Association for Computational Linguistics (Acl 2019): pp. 902-914
Conference or Workshop Item
Dufter, Philipp; Schmitt, Martin and Schütze, Hinrich
(December 2020):
Increasing Learning Efficiency of Self-Attention Networks through Direct Position Interactions, Learnable Temperature, and Convoluted Attention.
The 28th International Conference on Computational Linguistics, Online, 8. - 13. Dezember 2020.
In:
[PDF, 395kB]
Schmitt, Martin; Steinheber, Simon and Schreiber, Konrad
(October 2018):
Joint Aspect and Polarity Classification for Aspect-based Sentiment Analysis with End-to-End Neural Networks.
2018 Conference on Empirical Methods in Natural Language Processing; EMNLP 2018, Brussels, Belgium, 31. October - 02. November 2018.
In:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing.
Stroudsburg PA: Association for Computational Linguistics. pp. 1109-1114
[PDF, 193kB]
Dufter, Philipp; Zhao, Mengjie; Schmitt, Martin; Fraser, Alexander and Schütze, Hinrich
(July 2018):
Embedding Learning Through Multilingual Concept Induction.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Melbourne, Australia, July 15-20, 2018.
In:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics,
Vol. 1.
Association for Computational Linguistics. pp. 1520-1530
[PDF, 453kB]