66 citations · 67 across the 3 of their papers we have counts for
5 papers
Large Language Models for Summarizing Czech Historical Documents and Beyond
Václav Tran, Jakub Šmíd, Jiří Martínek +2
Text summarization is the task of shortening a larger body of text into a concise version while retaining its essential meaning and key information. While summarization has been si…
UWBa at SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval
Ladislav Lenc, Daniel Cífka, Jiří Martínek +2
This paper presents a zero-shot system for fact-checked claim retrieval. We employed several state-of-the-art large language models to obtain text embeddings. The models were then…
Well-calibrated Confidence Measures for Multi-label Text Classification with a Large Number of Labels
Lysimachos Maltoudoglou, Andreas Paisios, Ladislav Lenc +3
We extend our previous work on Inductive Conformal Prediction (ICP) for multi-label text classification and present a novel approach for addressing the computational inefficiency o…
Re-ranking for Writer Identification and Writer Retrieval
Simon Jordan, Mathias Seuret, Pavel Král +6
Automatic writer identification is a common problem in document analysis. State-of-the-art methods typically focus on the feature extraction step with traditional or deep-learning-…
Multi-lingual Dialogue Act Recognition with Deep Learning Methods
Jiří Martínek, Pavel Král, Ladislav Lenc +1
This paper deals with multi-lingual dialogue act (DA) recognition. The proposed approaches are based on deep neural networks and use word2vec embeddings for word representation. Tw…