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20202025
most citedImproving Aspect-Based Sentiment with End-to-End Semantic Role Labeling Model

1 citations · 1 across the 2 of their papers we have counts for

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cs.CL2025

Czech Dataset for Complex Aspect-Based Sentiment Analysis Tasks

Jakub Šmíd, Pavel Přibáň, Ondřej Pražák +1

In this paper, we introduce a novel Czech dataset for aspect-based sentiment analysis (ABSA), which consists of 3.1K manually annotated reviews from the restaurant domain. The data…

cs.CL20231 cited

Improving Aspect-Based Sentiment with End-to-End Semantic Role Labeling Model

Pavel Přibáň, Ondřej Pražák

This paper presents a series of approaches aimed at enhancing the performance of Aspect-Based Sentiment Analysis (ABSA) by utilizing extracted semantic information from a Semantic…

cs.CL2021

Czert -- Czech BERT-like Model for Language Representation

Jakub Sido, Ondřej Pražák, Pavel Přibáň +3

This paper describes the training process of the first Czech monolingual language representation models based on BERT and ALBERT architectures. We pre-train our models on more than…

cs.CL2020

UWB at SemEval-2020 Task 1: Lexical Semantic Change Detection

Ondřej Pražák, Pavel Přibáň, Stephen Taylor +1

In this paper, we describe our method for the detection of lexical semantic change, i.e., word sense changes over time. We examine semantic differences between specific words in tw…

cs.CL2020

UWB @ DIACR-Ita: Lexical Semantic Change Detection with CCA and Orthogonal Transformation

Ondřej Pražák, Pavel Přibáň, Stephen Taylor

In this paper, we describe our method for detection of lexical semantic change (i.e., word sense changes over time) for the DIACR-Ita shared task, where we ranked . We exam…