It Cannot Be Right If It Was Written by AI: On Lawyers' Preferences of Documents Perceived as Authored by an LLM vs a Human

no code implementations • 9 Jul 2024 • Jakub Harasta, Tereza Novotná, Jaromir Savelka

Large Language Models (LLMs) enable a future in which certain types of legal documents may be generated automatically.

Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains

1 code implementation • 15 Dec 2021 • Jaromir Savelka, Hannes Westermann, Karim Benyekhlef, Charlotte S. Alexander, Jayla C. Grant, David Restrepo Amariles, Rajaa El Hamdani, Sébastien Meeùs, Michał Araszkiewicz, Kevin D. Ashley, Alexandra Ashley, Karl Branting, Mattia Falduti, Matthias Grabmair, Jakub Harašta, Tereza Novotná, Elizabeth Tippett, Shiwanni Johnson

In this paper, we examine the use of multi-lingual sentence embeddings to transfer predictive models for functional segmentation of adjudicatory decisions across jurisdictions, legal systems (common and civil law), languages, and domains (i. e. contexts).

Segmentation Sentence +1

Citation Data of Czech Apex Courts

1 code implementation • 6 Feb 2020 • Jakub Harašta, Tereza Novotná, Jaromír Šavelka

In this paper, we introduce the citation data of the Czech apex courts (Supreme Court, Supreme Administrative Court and Constitutional Court).

The Czech Court Decisions Corpus (CzCDC): Availability as the First Step

1 code implementation • 21 Oct 2019 • Tereza Novotná, Jakub Harašta

These are further exacerbated by a lack of inter-court standard in the terms of the data format in which courts provide their decisions.