Papers by Nils Holzenberger

2 papers
CLERC: A Dataset for U. S. Legal Case Retrieval and Retrieval-Augmented Analysis Generation (2025.findings-naacl)

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Challenge: a dataset of case law is used to train and evaluate models for writing legal analyses . current approaches struggle to find relevant cases and generate legal analyses, authors say .
Approach: They build a dataset of case law to support information retrieval and retrieval-augmented generation.
Outcome: The proposed dataset supports two important backbone tasks: retrieval (IR) and retrieval-augmented generation (RAG).
Factoring Statutory Reasoning as Language Understanding Challenges (2021.acl-long)

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Challenge: Statutory reasoning is the task of determining whether a legal statute applies to a text description of a case.
Approach: They propose to decompose statutory reasoning into four types of language-understanding challenge problems using Prolog programming.
Outcome: The proposed framework improves on existing baselines and finer-grained models.

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