23 citations · 68 across the 8 of their papers we have counts for
6 papers · 1 filter
Analyzing Images of Legal Documents: Toward Multi-Modal LLMs for Access to Justice
Hannes Westermann, Jaromir Savelka
Interacting with the legal system and the government requires the assembly and analysis of various pieces of information that can be spread across different (paper) documents, such…
From Text to Structure: Using Large Language Models to Support the Development of Legal Expert Systems
Samyar Janatian, Hannes Westermann, Jinzhe Tan +2
Encoding legislative text in a formal representation is an important prerequisite to different tasks in the field of AI & Law. For example, rule-based expert systems focused on leg…
LLMediator: GPT-4 Assisted Online Dispute Resolution
Hannes Westermann, Jaromir Savelka, Karim Benyekhlef
In this article, we introduce LLMediator, an experimental platform designed to enhance online dispute resolution (ODR) by utilizing capabilities of state-of-the-art large language…
Sentence Embeddings and High-speed Similarity Search for Fast Computer Assisted Annotation of Legal Documents
Hannes Westermann, Jaromir Savelka, Vern R. Walker +2
Human-performed annotation of sentences in legal documents is an important prerequisite to many machine learning based systems supporting legal tasks. Typically, the annotation is…
Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains
Jaromir Savelka, Hannes Westermann, Karim Benyekhlef +15
In this paper, we examine the use of multi-lingual sentence embeddings to transfer predictive models for functional segmentation of adjudicatory decisions across jurisdictions, leg…
Cross-Domain Generalization and Knowledge Transfer in Transformers Trained on Legal Data
Jaromir Savelka, Hannes Westermann, Karim Benyekhlef
We analyze the ability of pre-trained language models to transfer knowledge among datasets annotated with different type systems and to generalize beyond the domain and dataset the…