Search Results for author: Jan Šedivý

Found 10 papers, 4 papers with code

Metric Learning and Adaptive Boundary for Out-of-Domain Detection

1 code implementation22 Apr 2022 Petr Lorenc, Tommaso Gargiani, Jan Pichl, Jakub Konrád, Petr Marek, Ondřej Kobza, Jan Šedivý

Based on the open-world environment, we often encounter the situation that the training and test data are sampled from different distributions.

Metric Learning Open Intent Detection +1

Alquist 4.0: Towards Social Intelligence Using Generative Models and Dialogue Personalization

no code implementations16 Sep 2021 Jakub Konrád, Jan Pichl, Petr Marek, Petr Lorenc, Van Duy Ta, Ondřej Kobza, Lenka Hýlová, Jan Šedivý

In this work, we present the principles and inner workings of individual components of the open-domain dialogue system Alquist developed within the Alexa Prize Socialbot Grand Challenge 4 and the experiments we have conducted to evaluate them.

Do We Need Online NLU Tools?

1 code implementation19 Nov 2020 Petr Lorenc, Petr Marek, Jan Pichl, Jakub Konrád, Jan Šedivý

In this paper, we suggest criteria to choose the best intent recognition algorithm for an application.

Intent Recognition

Alquist 3.0: Alexa Prize Bot Using Conversational Knowledge Graph

no code implementations6 Nov 2020 Jan Pichl, Petr Marek, Jakub Konrád, Petr Lorenc, Van Duy Ta, Jan Šedivý

The third version of the open-domain dialogue system Alquist developed within the Alexa Prize 2020 competition is designed to conduct coherent and engaging conversations on popular topics.

Alquist 2.0: Alexa Prize Socialbot Based on Sub-Dialogue Models

no code implementations6 Nov 2020 Jan Pichl, Petr Marek, Jakub Konrád, Martin Matulík, Jan Šedivý

This paper presents the second version of the dialogue system named Alquist competing in Amazon Alexa Prize 2018.

Dialogue Management Management

Alquist: The Alexa Prize Socialbot

no code implementations18 Apr 2018 Jan Pichl, Petr Marek, Jakub Konrád, Martin Matulík, Hoang Long Nguyen, Jan Šedivý

This paper describes a new open domain dialogue system Alquist developed as part of the Alexa Prize competition for the Amazon Echo line of products.

BIG-bench Machine Learning

Sentence Pair Scoring: Towards Unified Framework for Text Comprehension

1 code implementation19 Mar 2016 Petr Baudiš, Jan Pichl, Tomáš Vyskočil, Jan Šedivý

We review the task of Sentence Pair Scoring, popular in the literature in various forms - viewed as Answer Sentence Selection, Semantic Text Scoring, Next Utterance Ranking, Recognizing Textual Entailment, Paraphrasing or e. g. a component of Memory Networks.

Natural Language Inference Reading Comprehension +1

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