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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 30 1 USCORE: An Effective Approach to Fully Unsupervised Evaluation Metrics for Machine Translation ... Belouadi, Jonas; Eger, Steffen. - : arXiv, 2022 BASE Show details 2 Constrained Density Matching and Modeling for Cross-lingual Alignment of Contextualized Representations ... Zhao, Wei; Eger, Steffen. - : arXiv, 2022 BASE Show details 3 Towards Explainable Evaluation Metrics for Natural Language Generation ... Leiter, Christoph; Lertvittayakumjorn, Piyawat; Fomicheva, Marina; Zhao, Wei; Gao, Yang; Eger, Steffen. - : arXiv, 2022 Abstract: Unlike classical lexical overlap metrics such as BLEU, most current evaluation metrics (such as BERTScore or MoverScore) are based on black-box language models such as BERT or XLM-R. They often achieve strong correlations with human judgments, but recent research indicates that the lower-quality classical metrics remain dominant, one of the potential reasons being that their decision processes are transparent. To foster more widespread acceptance of the novel high-quality metrics, explainability thus becomes crucial. In this concept paper, we identify key properties and propose key goals of explainable machine translation evaluation metrics. We also provide a synthesizing overview over recent approaches for explainable machine translation metrics and discuss how they relate to those goals and properties. Further, we conduct own novel experiments, which (among others) find that current adversarial NLP techniques are unsuitable for automatically identifying limitations of high-quality black-box evaluation ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://arxiv.org/abs/2203.11131 https://dx.doi.org/10.48550/arxiv.2203.11131 BASE Hide details 4 End-to-end style-conditioned poetry generation: What does it take to learn from examples alone? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Eger, Steffen. - : Underline Science Inc., 2021 BASE Show details 5 Better than Average: Paired Evaluation of NLP systems ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Eger, Steffen; Peyrard, Maxime. - : Underline Science Inc., 2021 BASE Show details 6 Changes in European Solidarity Before and During COVID-19: Evidence from a Large Crowd- and Expert-Annotated Twitter Dataset ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Eger, Steffen; Grunow, Daniela. - : Underline Science Inc., 2021 BASE Show details 7 BERT-Defense: A Probabilistic Model Based on BERT to Combat Cognitively Inspired Orthographic Adversarial Attacks ... Keller, Yannik; Mackensen, Jan; Eger, Steffen. - : arXiv, 2021 BASE Show details 8 Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors ... Kaster, Marvin; Zhao, Wei; Eger, Steffen. - : arXiv, 2021 BASE Show details 9 Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Eger, Steffen; Kaster, Marvin. - : Underline Science Inc., 2021 BASE Show details 10 Inducing Language-Agnostic Multilingual Representations ... Zhao, Wei; Eger, Steffen; Bjerva, Johannes. - : arXiv, 2020 BASE Show details 11 Probing Multilingual BERT for Genetic and Typological Signals ... Rama, Taraka; Beinborn, Lisa; Eger, Steffen. - : arXiv, 2020 BASE Show details 12 On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ... Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : arXiv, 2020 BASE Show details 13 How to Probe Sentence Embeddings in Low-Resource Languages: On Structural Design Choices for Probing Task Evaluation ... Eger, Steffen; Daxenberger, Johannes; Gurevych, Iryna. - : arXiv, 2020 BASE Show details 14 Vec2Sent: Probing Sentence Embeddings With Natural Language Generation ... The 28th International Conference on Computational Linguistics 2020; Eger, Steffen; Kerscher, Martin. - : Underline Science Inc., 2020 BASE Show details 15 From Hero to Zéroe: A Benchmark of Low-Level Adversarial Attacks ... Eger, Steffen; Benz, Yannik. - : arXiv, 2020 BASE Show details 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 BASE Show details 17 On aligning OpenIE extractions with Knowledge Bases: A case study Gashteovski, Kiril; Gemulla, Rainer; Kotnis, Bhushan. - : Association for Computational Linguistics (ACL), 2020 BASE Show details 18 Semantic Change and Emerging Tropes In a Large Corpus of New High German Poetry ... Haider, Thomas; Eger, Steffen. - : arXiv, 2019 BASE Show details 19 Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need! ... Eger, Steffen; Daxenberger, Johannes; Stab, Christian. - : arXiv, 2018 BASE Show details 20 What is the Essence of a Claim? Cross-Domain Claim Identification ... Daxenberger, Johannes; Eger, Steffen; Habernal, Ivan. - : arXiv, 2017 BASE Show details Page: 1 2

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