8 citations · 13 across the 6 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…