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Fairlex: A multilingual benchmark for evaluating fairness in legal text processing ...
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Fairlex: A multilingual benchmark for evaluating fairness in legal text processing ...
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FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing ...
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One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia ...
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Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction ...
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Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models ...
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YET LIE THEY DO: A LIST-EXPERIMENT FOR ESTIMATING ANTI-IMMIGRANT SENTIMENT AND SOCIAL DESIRABILITY BIAS
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Modified Gravity and Cosmology: An Update by the CANTATA Network
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In: https://hal.archives-ouvertes.fr/hal-03261155 ; 2021 (2021)
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The Dawn of the Human-Machine Era: A forecast of new and emerging language technologies.
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In: https://hal.archives-ouvertes.fr/hal-03230287 ; 2021 (2021)
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UNITEX 3.3 User Manual
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In: https://hal.archives-ouvertes.fr/hal-03589580 ; 2021 (2021)
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UNITEX 3.3 Manuel d'utilisation
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In: https://hal.archives-ouvertes.fr/hal-03589598 ; 2021 (2021)
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Modified Gravity and Cosmology: An Update by the CANTATA Network ...
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UnibucKernel: Geolocating Swiss German Jodels Using Ensemble Learning ...
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Abstract:
In this work, we describe our approach addressing the Social Media Variety Geolocation task featured in the 2021 VarDial Evaluation Campaign. We focus on the second subtask, which is based on a data set formed of approximately 30 thousand Swiss German Jodels. The dialect identification task is about accurately predicting the latitude and longitude of test samples. We frame the task as a double regression problem, employing an XGBoost meta-learner with the combined power of a variety of machine learning approaches to predict both latitude and longitude. The models included in our ensemble range from simple regression techniques, such as Support Vector Regression, to deep neural models, such as a hybrid neural network and a neural transformer. To minimize the prediction error, we approach the problem from a few different perspectives and consider various types of features, from low-level character n-grams to high-level BERT embeddings. The XGBoost ensemble resulted from combining the power of the ... : This paper describes our system for the SMG-CH shared task of the VarDial 2021 Evaluation Campaign. arXiv admin note: text overlap with arXiv:2010.03614 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2102.09379 https://dx.doi.org/10.48550/arxiv.2102.09379
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Towards Human-Free Automatic Quality Evaluation of German Summarization ...
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Linguistically Informed Masking for Representation Learning in the Patent Domain ...
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Persuasive Natural Language Generation -- A Literature Review ...
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