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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 ...
Abstract: Cross-lingual representations have the potential to make NLP techniques available to the vast majority of languages in the world. However, they currently require large pretraining corpora or access to typologically similar languages. In this work, we address these obstacles by removing language identity signals from multilingual embeddings. We examine three approaches for this: (i) re-aligning the vector spaces of target languages (all together) to a pivot source language; (ii) removing language-specific means and variances, which yields better discriminativeness of embeddings as a by-product; and (iii) increasing input similarity across languages by removing morphological contractions and sentence reordering. We evaluate on XNLI and reference-free MT across 19 typologically diverse languages. Our findings expose the limitations of these approaches -- unlike vector normalization, vector space re-alignment and text normalization do not achieve consistent gains across encoders and languages. Due to the ... : *SEM2021 Camera Ready ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2008.09112
https://arxiv.org/abs/2008.09112
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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. - : Association for Computational Linguistics (ACL), 2020
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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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