📖 NLP Understanding

🤖 AAAI2026 · 1 paper notes

📌 Same area in other venues: 🔬 ICLR2026 (2) · 💬 ACL2026 (34) · 🧪 ICML2026 (2) · 🧠 NeurIPS2025 (3) · 📹 ICCV2025 (1) · 🧪 ICML2025 (1)

Language Models and Logic Programs for Trustworthy Tax Reasoning

This paper reframes tax law reasoning as a semantic parsing task, where LLMs translate statutory text and case facts into Prolog logic programs that are subsequently executed by a symbolic solver. By combining gold-standard statute translations, retrieval-augmented case examples, and self-consistency checks, the system achieves 86/100 accuracy on the SARA dataset while reducing estimated deployment cost to $15.78 per person — less than 6% of the average U.S. tax filing cost.