Výsledky vyhledávání - "Štancl, Daniel"

Report

Siamese BERT-based Model for Web Search Relevance Ranking Evaluated on a New Czech Dataset

Autor: Kocián, Matěj, Náplava, Jakub, Štancl, Daniel, Kadlec, Vladimír

Web search engines focus on serving highly relevant results within hundreds of milliseconds. Pre-trained language transformer models such as BERT are therefore hard to use in this scenario due to their high computational demands. We present our real-

Externí odkaz: http://arxiv.org/abs/2112.01810

Zobrazit plný text záznamu

DIASER : une unification d'annotation pour les dialogues orientés tâche

Autor: Hudeček, Vojtěch, Schaub, Léon-Paul, Štancl, Daniel, Paroubek, Patrick, Ondrej Dusek

Publikováno v: Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)
Language Resources and Evaluation Conference (LREC2022)
Language Resources and Evaluation Conference (LREC2022), Jun 2022, Marseille, France
Ondrej Dusek

International audience; Every model is only as strong as the data that it is trained on. In this paper, we present a new dataset, obtained by merging four publicly available annotated corpora for task-oriented dialogues in several domains (MultiWOZ 2

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d3050473385ef10a9d61f0867b99ae5b
https://hal.science/hal-03713523

Zobrazit plný text záznamu

A Unifying View On Task-oriented Dialogue Annotation

Autor: Hudeček, Vojtěch, Štancl, Daniel, Dušek, Ondřej, Schaub, Léon-Paul, Paroubek, Patrick

Every model is only as strong as the data that it is trained on. In this paper, we present a new dataset, obtained by merging four publicly available annotated corpora for task-oriented dialogues in several domains (MultiWOZ 2.2, CamRest676, DSTC2 an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3719::1fda740811001b073b1ad49c9706e88a
https://hdl.handle.net/11346/BIBLIO@id=-1465947880108986498

Zobrazit plný text záznamu

Définition et détection des incohérences du système dans les dialogues orientés tâche

Autor: Schaub, Léon-Paul, Hudeček, Vojtěch, Štancl, Daniel, Ondrej Dusek, Paroubek, Patrick

Publikováno v: Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale
Traitement Automatique des Langues Naturelles
Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.142-152
Ondrej Dusek

International audience; Définition et détection des incohérences du système dans les dialogues orientés tâche. Nous présentons des expériences sur la détection automatique des comportements incohérents des systèmes de dialogues orientés t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::aecb0d3597bff91609fc97ff7942fa84
https://hal.science/hal-03265892/document

Zobrazit plný text záznamu

Predicting Financial Market Crashes using Log-periodic Oscillation and Critical Slowing Down

Autor: Štancl, Daniel

This bachelor thesis concerns itself with multiple objectives. First, to compare two apparently contradictory frameworks, namely the Log-periodic Power Law model and the Critical Slowing Down, suggested as being able to detect the end of financial bu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2186::4505ae3969edfe24c4779674790d4465
http://www.nusl.cz/ntk/nusl-397604

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání