Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: A Comparative Study

This study experimentally evaluates large language models (LLMs) for legal decision-making in Austrian and EU value‑added tax (VAT) law. It compares fine‑tuning and retrieval‑augmented generation (RAG) on textbook and real‑world tax consulting cases to identify optimal LLM configurations and assess legal‑reasoning abilities. Results show that properly configured LLMs can aid tax professionals with routine tasks and provide legally grounded justifications, though they are not yet ready for full automation due to challenges like hallucination and handling implicit client knowledge.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

• llms
• rag
• fine-tuning