activity
20162024
most citedRecurrent Neural Networks for Dialogue State Tracking

4 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

Automatic Metrics in Natural Language Generation: A Survey of Current Evaluation Practices

Patrícia Schmidtová, Saad Mahamood, Simone Balloccu +6

Automatic metrics are extensively used to evaluate natural language processing systems. However, there has been increasing focus on how they are used and reported by practitioners…

cs.CL2024

factgenie: A Framework for Span-based Evaluation of Generated Texts

Zdeněk Kasner, Ondřej Plátek, Patrícia Schmidtová +2

We present factgenie: a framework for annotating and visualizing word spans in textual model outputs. Annotations can capture various span-based phenomena such as semantic inaccura…

cs.CL2023

With a Little Help from the Authors: Reproducing Human Evaluation of an MT Error Detector

Ondřej Plátek, Mateusz Lango, Ondřej Dušek

This work presents our efforts to reproduce the results of the human evaluation experiment presented in the paper of Vamvas and Sennrich (2022), which evaluated an automatic system…

cs.CL20232 cited

Three Ways of Using Large Language Models to Evaluate Chat

Ondřej Plátek, Vojtěch Hudeček, Patricia Schmidtová +2

This paper describes the systems submitted by team6 for ChatEval, the DSTC 11 Track 4 competition. We present three different approaches to predicting turn-level qualities of chatb…

cs.CL20164 cited

Recurrent Neural Networks for Dialogue State Tracking

Ondřej Plátek, Petr Bělohlávek, Vojtěch Hudeček +1

This paper discusses models for dialogue state tracking using recurrent neural networks (RNN). We present experiments on the standard dialogue state tracking (DST) dataset, DSTC2.…