8 citations · 18 across the 10 of their papers we have counts for
13 papers
Findings of the Fifth Shared Task on Multilingual Coreference Resolution: Expanding Datasets for Long-Range Entities
Michal Novák, Miloslav Konopík, Anna Nedoluzhko +6
This paper describes the fifth edition of the Shared Task on Multilingual Coreference Resolution, held in conjunction with the CODI-CRAC 2026 workshop. Building on previous iterati…
Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches?
Michal Novák, Miloslav Konopík, Anna Nedoluzhko +6
The paper presents an overview of the fourth edition of the Shared Task on Multilingual Coreference Resolution, organized as part of the CODI-CRAC 2025 workshop. As in the previous…
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…
Findings of the Third Shared Task on Multilingual Coreference Resolution
Michal Novák, Barbora Dohnalová, Miloslav Konopík +7
The paper presents an overview of the third edition of the shared task on multilingual coreference resolution, held as part of the CRAC 2024 workshop. Similarly to the previous two…
Exploring Multiple Strategies to Improve Multilingual Coreference Resolution in CorefUD
Ondřej Pražák, Miloslav Konopík, Pavel Král
Coreference resolution, the task of identifying expressions in text that refer to the same entity, is a critical component in various natural language processing applications. This…
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…
End-to-end Multilingual Coreference Resolution with Mention Head Prediction
Ondřej Pražák, Miloslav Konopík
This paper describes our approach to the CRAC 2022 Shared Task on Multilingual Coreference Resolution. Our model is based on a state-of-the-art end-to-end coreference resolution sy…
MQDD: Pre-training of Multimodal Question Duplicity Detection for Software Engineering Domain
Jan Pašek, Jakub Sido, Miloslav Konopík +1
This work proposes a new pipeline for leveraging data collected on the Stack Overflow website for pre-training a multimodal model for searching duplicates on question answering web…
Czech News Dataset for Semantic Textual Similarity
Jakub Sido, Michal Seják, Ondřej Pražák +2
This paper describes a novel dataset consisting of sentences with semantic similarity annotations. The data originate from the journalistic domain in the Czech language. We describ…
Multilingual Coreference Resolution with Harmonized Annotations
Ondřej Pražák, Miloslav Konopík, Jakub Sido
In this paper, we present coreference resolution experiments with a newly created multilingual corpus CorefUD. We focus on the following languages: Czech, Russian, Polish, German,…
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…
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…
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…