activity
20162022
most citedAlquist 2.0: Alexa Prize Socialbot Based on Sub-Dialogue Models

12 citations · 41 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2022

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

Petr Lorenc, Tommaso Gargiani, Jan Pichl +4

Conversational agents are usually designed for closed-world environments. Unfortunately, users can behave unexpectedly. Based on the open-world environment, we often encounter the…

cs.CL202111 cited

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

Jakub Konrád, Jan Pichl, Petr Marek +5

The open domain-dialogue system Alquist has a goal to conduct a coherent and engaging conversation that can be considered as one of the benchmarks of social intelligence. The fourt…

cs.CL202111 cited

Text Summarization of Czech News Articles Using Named Entities

Petr Marek, Štěpán Müller, Jakub Konrád +3

The foundation for the research of summarization in the Czech language was laid by the work of Straka et al. (2018). They published the SumeCzech, a large Czech news-based summariz…

cs.CL2020

Do We Need Online NLU Tools?

Petr Lorenc, Petr Marek, Jan Pichl +2

The intent recognition is an essential algorithm of any conversational AI application. It is responsible for the classification of an input message into meaningful classes. In many…

cs.CL20207 cited

Alquist 3.0: Alexa Prize Bot Using Conversational Knowledge Graph

Jan Pichl, Petr Marek, Jakub Konrád +3

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…

cs.CL202012 cited

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

Jan Pichl, Petr Marek, Jakub Konrád +2

This paper presents the second version of the dialogue system named Alquist competing in Amazon Alexa Prize 2018. We introduce a system leveraging ontology-based topic structure ca…