11 papers
From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMs
Jiawen Wang, Pritha Gupta, Ivan Habernal +3
Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-source LLMs are increasingly adopted in h…
HiPS: Hierarchical PDF Segmentation of Doctrinal Legal Books
Sabine Wehnert, Harikrishnan Changaramkulath, Ivan Habernal
PDF parsers have recently improved on page-level layout understanding. However, recovering a document-global section hierarchy with reliable boundaries remains brittle for deeply s…
MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems
Arda Yüksel, Gabriel Thiem, Susanne Walter +3
Industry classification schemes are integral parts of public and corporate databases as they classify businesses based on economic activity. Due to the size of the company register…
Legal Experts Disagree With Rationale Extraction Techniques for Explaining ECtHR Case Outcome Classification
Mahammad Namazov, Tomáš Koref, Ivan Habernal
Interpretability is critical for applications of large language models (LLMs) in the legal domain, where trust and transparency are essential. A central NLP task in this setting is…
Mining Legal Arguments to Study Judicial Formalism
TomᚠKoref, Tomáš Koref, Lena Held +4
Courts must justify their decisions, but systematically analyzing judicial reasoning at scale remains difficult. This study tests claims about formalistic judging in Central and Ea…
The Conundrum of Trustworthy Research on Attacking Personally Identifiable Information Removal Techniques
Sebastian Ochs, Ivan Habernal
Removing personally identifiable information (PII) from texts is necessary to comply with various data protection regulations and to enable data sharing without compromising privac…