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

arXiv:2507.08468 · cs.CL · Submitted 2025-07-11 · Read on arXiv

cs.CL

Submitted: 2025-07-11

Updated: 2026-09-02

Code: https://github.com/pymupdf/RAG

Terminology

• RAG — 77× in this paper · explained in 3 episodes
• Accuracy — 57× in this paper · explained in 1 episode
• Fine-Tuning — 51× in this paper · explained in 5 episodes
• Prompt Engineering — 5× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 4× in this paper · explained in 6 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Retrieval-Augmented Generation (RAG) — 3× in this paper · explained in 16 episodes
• Adaptability — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Explainability — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Knowledge Graph — 2× in this paper · explained in 7 episodes
• Vector Representations — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes

Sources

• Large Language Models are legal but they are not: Making the case for a powerful LegalLLM
• LawBench: Benchmarking Legal Knowledge of Large Language Models
• A Short Survey of Viewing Large Language Models in Legal Aspect
• DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services
• Better Call GPT, Comparing Large Language Models Against Lawyers
• Retrieval-Augmented Generation for Large Language Models: A Survey

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