# A Law Reasoning Benchmark for LLM with Tree-Organized Structures including Factum Probandum, Evidence and Experiences

arXiv: https://arxiv.org/abs/2503.00841 · HTML: https://mlsanity.com/paper/2503.00841/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning.
- Builds on 7 of its 53 references that are in the map.
- First posted on arXiv 2 Mar 2025.

## Placed in

- LLM reasoning / [Reasoning for agents, planning and code](https://mlsanity.com/lr/reasoning-for-agents-planning-and-code/)

## Builds on (most cited first, 7 of 7)

- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [Qwen2.5 Technical Report](https://mlsanity.com/paper/2412.15115/) (2024)
- [DeepSeek-V3 Technical Report](https://mlsanity.com/paper/2412.19437/) (2024)
- [SaulLM-7B: A pioneering Large Language Model for Law](https://mlsanity.com/paper/2403.03883/) (2024)
- [Lawyer LLaMA Technical Report](https://mlsanity.com/paper/2305.15062/) (2023)
- [Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration](https://mlsanity.com/paper/2310.09241/) (2023)
- [InternLM-Law: An Open Source Chinese Legal Large Language Model](https://mlsanity.com/paper/2406.14887/) (2024)

## Built on by (most cited first, 7 of 7)

- [Benchmarking Multi-Step Legal Reasoning and Analyzing Chain-of-Thought Effects in Large Language Models](https://mlsanity.com/paper/2511.07979/) (2025)
- [CML-Bench: A Framework for Evaluating and Enhancing LLM-Powered Movie Scripts Generation](https://mlsanity.com/paper/2510.06231/) (2025)
- [The Hidden Structure -- Improving Legal Document Understanding Through Explicit Text Formatting](https://mlsanity.com/paper/2505.12837/) (2025)
- [Agent Benchmarks Fail Public Sector Requirements](https://mlsanity.com/paper/2601.20617/) (2026)
- [Diverse Thinking Schemata Elicit Better Reasoning in Large Language Models](https://mlsanity.com/paper/2606.08974/) (2026)
- [From Policy to Logic for Efficient and Interpretable Coverage Assessment](https://mlsanity.com/paper/2601.01266/) (2026)
- [JusticeAxis: Benchmarking Legal Judgment between Rigid Rule Application and Ungrounded Discretion](https://mlsanity.com/paper/2610.00353/) (2026)

## Abstract (arXiv)

While progress has been made in legal applications, law reasoning, crucial for fair adjudication, remains unexplored. We propose a transparent law reasoning schema enriched with hierarchical factum probandum, evidence, and implicit experience, enabling public scrutiny and preventing bias. Inspired by this schema, we introduce the challenging task, which takes a textual case description and outputs a hierarchical structure justifying the final decision. We also create the first crowd-sourced dataset for this task, enabling comprehensive evaluation. Simultaneously, we propose an agent framework that employs a comprehensive suite of legal analysis tools to address the challenge task. This benchmark paves the way for transparent and accountable AI-assisted law reasoning in the ``Intelligent Court''.