Piotr Przybyła


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Investigating Text Simplification Evaluation
Laura Vásquez-Rodríguez | Matthew Shardlow | Piotr Przybyła | Sophia Ananiadou
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

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HOMADOS at SemEval-2021 Task 6: Multi-Task Learning for Propaganda Detection
Konrad Kaczyński | Piotr Przybyła
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)

Among the tasks motivated by the proliferation of misinformation, propaganda detection is particularly challenging due to the deficit of fine-grained manual annotations required to train machine learning models. Here we show how data from other related tasks, including credibility assessment, can be leveraged in multi-task learning (MTL) framework to accelerate the training process. To that end, we design a BERT-based model with multiple output layers, train it in several MTL scenarios and perform evaluation against the SemEval gold standard.


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Multi-Word Lexical Simplification
Piotr Przybyła | Matthew Shardlow
Proceedings of the 28th International Conference on Computational Linguistics

In this work we propose the task of multi-word lexical simplification, in which a sentence in natural language is made easier to understand by replacing its fragment with a simpler alternative, both of which can consist of many words. In order to explore this new direction, we contribute a corpus (MWLS1), including 1462 sentences in English from various sources with 7059 simplifications provided by human annotators. We also propose an automatic solution (Plainifier) based on a purpose-trained neural language model and evaluate its performance, comparing to human and resource-based baselines.


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NaCTeM at SemEval-2016 Task 1: Inferring sentence-level semantic similarity from an ensemble of complementary lexical and sentence-level features
Piotr Przybyła | Nhung T. H. Nguyen | Matthew Shardlow | Georgios Kontonatsios | Sophia Ananiadou
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)


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Question Analysis for Polish Question Answering
Piotr Przybyła
51st Annual Meeting of the Association for Computational Linguistics Proceedings of the Student Research Workshop