no code implementations • 28 Jun 2016 • Ondřej Plátek, Petr Bělohlávek, Vojtěch Hudeček, Filip Jurčíček
This paper discusses models for dialogue state tracking using recurrent neural networks (RNN).
1 code implementation • EMNLP (NLP4ConvAI) 2021 • Jonáš Kulhánek, Vojtěch Hudeček, Tomáš Nekvinda, Ondřej Dušek
Our model substantially outperforms the baseline on the MultiWOZ data and shows competitive performance with state of the art in both automatic and human evaluation.
Ranked #3 on End-To-End Dialogue Modelling on MULTIWOZ 2.0 (using extra training data)
1 code implementation • 22 Sep 2022 • Vojtěch Hudeček, Ondřej Dušek
We present a novel architecture for explainable modeling of task-oriented dialogues with discrete latent variables to represent dialogue actions.
no code implementations • 13 Apr 2023 • Vojtěch Hudeček, Ondřej Dušek
Instructions-tuned Large Language Models (LLMs) gained recently huge popularity thanks to their ability to interact with users through conversation.
2 code implementations • 12 Aug 2023 • Ondřej Plátek, Vojtěch Hudeček, Patricia Schmidtová, Mateusz Lango, Ondřej Dušek
This paper describes the systems submitted by team6 for ChatEval, the DSTC 11 Track 4 competition.
1 code implementation • LREC 2022 • Vojtěch Hudeček, Leon-paul Schaub, Daniel Stancl, Patrick Paroubek, Ondřej Dušek
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 and Schema-Guided Dialogue Dataset).