collaborators

9 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

Teaching LLMs at Charles University: Assignments and Activities

Jindřich Helcl, Zdeněk Kasner, Ondřej Dušek +4

This paper presents teaching materials, particularly assignments and ideas for classroom activities, from a new course on large language models (LLMs) taught at Charles University.…

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.CL2024

Text Style Transfer: An Introductory Overview

Sourabrata Mukherjee, Ondrej Dušek

Text Style Transfer (TST) is a pivotal task in natural language generation to manipulate text style attributes while preserving style-independent content. The attributes targeted i…

cs.CL202419 cited

Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs

Simone Balloccu, Patrícia Schmidtová, Mateusz Lango +1

Natural Language Processing (NLP) research is increasingly focusing on the use of Large Language Models (LLMs), with some of the most popular ones being either fully or partially c…

cs.CL2023

Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text Generation

Mateusz Lango, Ondřej Dušek

Hallucination of text ungrounded in the input is a well-known problem in neural data-to-text generation. Many methods have been proposed to mitigate it, but they typically require…