40.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Ludwig-Maximilians-Universität MünchenDE49 papers
- FZU ‒ Institute of Physics of the Academy of Sciences of the Czech RepublicCZ39 papers
- Czech Technical University in PragueCZ35 papers
- Charles UniversityCZ34 papers
- Centre National de la Recherche ScientifiqueFR31 papers
- Czech Academy of SciencesCZ28 papers
- Paul Scherrer InstituteCH27 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR24 papers
- Université Paris-SaclayFR20 papers
- CEA Paris-SaclayFR19 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di GenovaIT19 papers
- HUN-REN Wigner Research Centre for PhysicsHU18 papers
23 papers · 1 filter
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…
Large Language Models for Summarizing Czech Historical Documents and Beyond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…
Advancing Cross-lingual Aspect-Based Sentiment Analysis with LLMs and Constrained Decoding for Sequence-to-Sequence Models
Jakub Šmíd, Pavel Přibáň, Pavel Král
Aspect-based sentiment analysis (ABSA) has made significant strides, yet challenges remain for low-resource languages due to the predominant focus on English. Current cross-lingual…
Cross-lingual Aspect-Based Sentiment Analysis: A Survey on Tasks, Approaches, and Challenges
Jakub Šmíd, Pavel Král
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that focuses on understanding opinions at the aspect level, including sentiment towards specific as…
LACA: Improving Cross-lingual Aspect-Based Sentiment Analysis with LLM Data Augmentation
Jakub Šmíd, Pavel Přibáň, Pavel Král
Cross-lingual aspect-based sentiment analysis (ABSA) involves detailed sentiment analysis in a target language by transferring knowledge from a source language with available annot…
UWB at WASSA-2024 Shared Task 2: Cross-lingual Emotion Detection
Jakub Šmíd, Pavel Přibáň, Pavel Král
This paper presents our system built for the WASSA-2024 Cross-lingual Emotion Detection Shared Task. The task consists of two subtasks: first, to assess an emotion label from six p…
LLaMA-Based Models for Aspect-Based Sentiment Analysis
Jakub Šmíd, Pavel Přibáň, Pavel Král
While large language models (LLMs) show promise for various tasks, their performance in compound aspect-based sentiment analysis (ABSA) tasks lags behind fine-tuned models. However…
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…
Transfer Learning of Transformer-based Speech Recognition Models from Czech to Slovak
Jan Lehečka, Josef V. Psutka, Josef Psutka
In this paper, we are comparing several methods of training the Slovak speech recognition models based on the Transformers architecture. Specifically, we are exploring the approach…
Spoken Term Detection and Relevance Score Estimation using Dot-Product of Pronunciation Embeddings
Jan Švec, Luboš Šmídl, Josef V. Psutka +1
The paper describes a novel approach to Spoken Term Detection (STD) in large spoken archives using deep LSTM networks. The work is based on the previous approach of using Siamese n…
Deep LSTM Spoken Term Detection using Wav2Vec 2.0 Recognizer
Jan Švec, Jan Lehečka, Luboš Šmídl
In recent years, the standard hybrid DNN-HMM speech recognizers are outperformed by the end-to-end speech recognition systems. One of the very promising approaches is the grapheme…
Linear Transformations for Cross-lingual Sentiment Analysis
Pavel Přibáň, Jakub Šmíd, Adam Mištera +1
This paper deals with cross-lingual sentiment analysis in Czech, English and French languages. We perform zero-shot cross-lingual classification using five linear transformations c…
Transformer-based Automatic Speech Recognition of Formal and Colloquial Czech in MALACH Project
Jan Lehečka, Josef V. Psutka, Josef Psutka
Czech is a very specific language due to its large differences between the formal and the colloquial form of speech. While the formal (written) form is used mainly in official docu…
Are the Multilingual Models Better? Improving Czech Sentiment with Transformers
Pavel Přibáň, Josef Steinberger
In this paper, we aim at improving Czech sentiment with transformer-based models and their multilingual versions. More concretely, we study the task of polarity detection for the C…
Comparison of Czech Transformers on Text Classification Tasks
Jan Lehečka, Jan Švec
In this paper, we present our progress in pre-training monolingual Transformers for Czech and contribute to the research community by releasing our models for public. The need for…
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…
On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition
Christophe Cerisara, Pavel Kral, Ladislav Lenc
Dialogue act recognition is an important component of a large number of natural language processing pipelines. Many research works have been carried out in this area, but relativel…
Cross-lingual Word Analogies using Linear Transformations between Semantic Spaces
Tomáš Brychcín, Stephen Eugene Taylor, Lukáš Svoboda
We generalize the word analogy task across languages, to provide a new intrinsic evaluation method for cross-lingual semantic spaces. We experiment with six languages within differ…
Deep Neural Networks for Czech Multi-label Document Classification
Ladislav Lenc, Pavel Král
This paper is focused on automatic multi-label document classification of Czech text documents. The current approaches usually use some pre-processing which can have negative impac…
Unsupervised Dialogue Act Induction using Gaussian Mixtures
Tomáš Brychcín, Pavel Král
This paper introduces a new unsupervised approach for dialogue act induction. Given the sequence of dialogue utterances, the task is to assign them the labels representing their fu…
New word analogy corpus for exploring embeddings of Czech words
Lukáš Svoboda, Tomáš Brychcín
The word embedding methods have been proven to be very useful in many tasks of NLP (Natural Language Processing). Much has been investigated about word embeddings of English words…
Latent Tree Language Model
Tomas Brychcin
In this paper we introduce Latent Tree Language Model (LTLM), a novel approach to language modeling that encodes syntax and semantics of a given sentence as a tree of word roles. T…