Publications

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69 Publications visible to you, out of a total of 69

Abstract

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Authors: Chloé Braud, Christian Hardmeier, Junyi Jessy Li, Annie Louis, Michael Strube, Amir Zeldes

Date Published: 10th Nov 2021

Publication Type: Proceedings

Abstract

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Author: Michael Strube

Date Published: 2021

Publication Type: InBook

Abstract

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Authors: Federico López, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard

Date Published: 2021

Publication Type: InProceedings

Abstract

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Authors: Federico Lopez, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard

Date Published: 2021

Publication Type: InProceedings

Abstract (Expand)

Pretrained language models, neural models pretrained on massive amounts of data, have established the state of the art in a range of NLP tasks. They are based on a modern machine-learning technique, the Transformer which relates all items simultaneously to capture semantic relations in sequences. However, it differs from what humans do. Humans read sentences one-by-one, incrementally. Can neural models benefit by interpreting texts incrementally as humans do? We investigate this question in coherence modeling. We propose a coherence model which interprets sentences incrementally to capture lexical relations between them. We compare the state of the art in each task, simple neural models relying on a pretrained language model, and our model in two downstream tasks. Our findings suggest that interpreting texts incrementally as humans could be useful to design more advanced models.

Authors: Sungho Jeon, Michael Strube

Date Published: 1st Dec 2020

Publication Type: InProceedings

Abstract

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Authors: Chloé Braud, Christian Hardmeier, Junyi Jessy Li, Annie Louis, Michael Strube

Date Published: 20th Nov 2020

Publication Type: Proceedings

Abstract

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Authors: Kevin Mathews, Michael Strube

Date Published: 11th May 2020

Publication Type: InProceedings

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