📖 NLP Understanding

🤖 AAAI2026 · 2 paper notes

📌 Same area in other venues: 💬 ACL2026 (14) · 🧠 NeurIPS2025 (2) · 📹 ICCV2025 (1)

🔥 Top topics: Reasoning ×2

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.

Understanding Syllogistic Reasoning in LLMs from Formal and Natural Language Perspectives

This work systematically evaluates 14 LLMs on 160 syllogisms using a dual-dimensional ground truth framework (syntactic validity + NLU believability), revealing that top models approach near-perfect performance on formal logic (99.6%) while performing at chance level on natural language believability (~52%)—the inverse of human reasoning patterns. 12 out of 14 models exhibit significant belief bias, and few-shot prompting degrades formal reasoning performance.