The AMELR workshop focuses on Legal Argument Mining (LAM) - using NLP to automatically detect legal arguments.
Recent developments in NLP and LAM have provided legal scholars with a powerful tool for studying reasoning patterns, interpretative theories, and biases across jurisdictions and legal systems.
The workshop gathers experts in computer science, AI & Law, legal theory, and empirical legal studies to address key challenges of LAM: creating training datasets, developing reliable models, establishing reproducibility standards, and integrating LAM into legal research.
The workshop aims to strengthen the emerging field of LAM and its role in empirical legal studies by sharing latest implementations, addressing core challenges, and establishing best practices.