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1
USCORE: An Effective Approach to Fully Unsupervised Evaluation Metrics for Machine Translation ...
Belouadi, Jonas; Eger, Steffen. - : arXiv, 2022
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2
Constrained Density Matching and Modeling for Cross-lingual Alignment of Contextualized Representations ...
Zhao, Wei; Eger, Steffen. - : arXiv, 2022
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3
Towards Explainable Evaluation Metrics for Natural Language Generation ...
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4
End-to-end style-conditioned poetry generation: What does it take to learn from examples alone? ...
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5
Better than Average: Paired Evaluation of NLP systems ...
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6
Changes in European Solidarity Before and During COVID-19: Evidence from a Large Crowd- and Expert-Annotated Twitter Dataset ...
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7
BERT-Defense: A Probabilistic Model Based on BERT to Combat Cognitively Inspired Orthographic Adversarial Attacks ...
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8
Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors ...
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9
Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors ...
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10
Inducing Language-Agnostic Multilingual Representations ...
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11
Probing Multilingual BERT for Genetic and Typological Signals ...
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12
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ...
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13
How to Probe Sentence Embeddings in Low-Resource Languages: On Structural Design Choices for Probing Task Evaluation ...
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14
Vec2Sent: Probing Sentence Embeddings With Natural Language Generation ...
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15
From Hero to Zéroe: A Benchmark of Low-Level Adversarial Attacks ...
Eger, Steffen; Benz, Yannik. - : arXiv, 2020
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16
On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation
Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : Association for Computational Linguistics, 2020
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17
On aligning OpenIE extractions with Knowledge Bases: A case study
Gashteovski, Kiril; Gemulla, Rainer; Kotnis, Bhushan; Hertling, Sven; Meilicke, Christian. - : Association for Computational Linguistics (ACL), 2020
Abstract: Open information extraction (OIE) is the task of extracting relations and their corresponding arguments from a natural language text in un- supervised manner. Outputs of such systems are used for downstream tasks such as ques- tion answering and automatic knowledge base (KB) construction. Many of these downstream tasks rely on aligning OIE triples with refer- ence KBs. Such alignments are usually eval- uated w.r.t. a specific downstream task and, to date, no direct manual evaluation of such alignments has been performed. In this paper, we directly evaluate how OIE triples from the OPIEC corpus are related to the DBpedia KB w.r.t. information content. First, we investigate OPIEC triples and DBpedia facts having the same arguments by comparing the information on the OIE surface relation with the KB rela- tion. Second, we evaluate the expressibility of general OPIEC triples in DBpedia. We in- vestigate whether—and, if so, how—a given OIE triple can be mapped to a single KB fact. We found that such mappings are not always possible because the information in the OIE triples tends to be more specific. Our evalua- tion suggests, however, that significant part of OIE triples can be expressed by means of KB formulas instead of individual facts.
Keyword: 004 Informatik
URL: https://madoc.bib.uni-mannheim.de/61524/1/On%20Aligning%20OpenIE%20Extractions%20with%20Knowledge%20Bases%20A%20Case%20Study.pdf
https://madoc.bib.uni-mannheim.de/61524
https://doi.org/10.18653/v1/2020.eval4nlp-1.14
https://madoc.bib.uni-mannheim.de/61524/
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18
Semantic Change and Emerging Tropes In a Large Corpus of New High German Poetry ...
Haider, Thomas; Eger, Steffen. - : arXiv, 2019
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19
Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need! ...
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20
What is the Essence of a Claim? Cross-Domain Claim Identification ...
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