# Multi-Agent Simulator Drives Language Models for Legal Intensive Interaction

arXiv: https://arxiv.org/abs/2502.06882 · HTML: https://mlsanity.com/paper/2502.06882/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use.
- Builds on 22 of its 41 references that are in the map.
- First posted on arXiv 8 Feb 2025.

## Placed in

- LLM agents and tool use / [Social simulation and multi-agent debate](https://mlsanity.com/agents/social-simulation-and-multi-agent-debate/)

## Builds on (most cited first, 22 of 22)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Efficient Memory Management for Large Language Model Serving with PagedAttention](https://mlsanity.com/paper/2309.06180/) (2023)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context](https://mlsanity.com/paper/2403.05530/) (2024)
- [Qwen2 Technical Report](https://mlsanity.com/paper/2407.10671/) (2024)
- [Baichuan 2: Open Large-scale Language Models](https://mlsanity.com/paper/2309.10305/) (2023)
- [Character-LLM: A Trainable Agent for Role-Playing](https://mlsanity.com/paper/2310.10158/) (2023)
- [Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias](https://mlsanity.com/paper/2306.15895/) (2023)
- [Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization](https://mlsanity.com/paper/2406.01171/) (2024)
- [DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services](https://mlsanity.com/paper/2309.11325/) (2023)
- [Can Large Language Model Agents Simulate Human Trust Behavior?](https://mlsanity.com/paper/2402.04559/) (2024)
- [AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios](https://mlsanity.com/paper/2410.19346/) (2024)
- [LexNLP: Natural language processing and information extraction for legal and regulatory texts](https://mlsanity.com/paper/1806.03688/) (2018)
- [Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks](https://mlsanity.com/paper/2407.09893/) (2024)
- [Identity-Driven Hierarchical Role-Playing Agents](https://mlsanity.com/paper/2407.19412/) (2024)
- [Learning Fine-grained Fact-Article Correspondence in Legal Cases](https://mlsanity.com/paper/2104.10726/) (2021)
- [Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/2112.06370/) (2021)
- [BEYOND DIALOGUE: A Profile-Dialogue Alignment Framework Towards General Role-Playing Language Model](https://mlsanity.com/paper/2408.10903/) (2024)
- [Fine-Tuned Large Language Model for Visualization System: A Study on Self-Regulated Learning in Education](https://mlsanity.com/paper/2407.20570/) (2024)
- [Human vs. LMMs: Exploring the Discrepancy in Emoji Interpretation and Usage in Digital Communication](https://mlsanity.com/paper/2401.08212/) (2024)

## Built on by (most cited first, 22 of 22)

- [FaithCoT-Bench: Benchmarking Instance-Level Faithfulness of Chain-of-Thought Reasoning](https://mlsanity.com/paper/2510.04040/) (2025)
- [A Survey on Agent Workflow -- Status and Future](https://mlsanity.com/paper/2508.01186/) (2025)
- [Ready Jurist One: Benchmarking Language Agents for Legal Intelligence in Dynamic Environments](https://mlsanity.com/paper/2507.04037/) (2025)
- [FinTeam: A Multi-Agent Collaborative Intelligence System for Comprehensive Financial Scenarios](https://mlsanity.com/paper/2507.10448/) (2025)
- [LLM Agents in Law: Taxonomy, Applications, and Challenges](https://mlsanity.com/paper/2601.06216/) (2026)
- [Data Science and Technology Towards AGI Part I: Tiered Data Management](https://mlsanity.com/paper/2602.09003/) (2026)
- [Human Values Matter: Investigating How Misalignment Shapes Collective Behaviors in LLM Agent Communities](https://mlsanity.com/paper/2604.05339/) (2026)
- [Law in Silico: Simulating Legal Society with LLM-Based Agents](https://mlsanity.com/paper/2510.24442/) (2025)
- [PAKTON: A Multi-Agent Framework for Question Answering in Long Legal Agreements](https://mlsanity.com/paper/2506.00608/) (2025)
- [LinguaGame: A Linguistically Grounded Game-Theoretic Paradigm for Multi-Agent Dialogue Generation](https://mlsanity.com/paper/2601.04516/) (2026)
- [PsyCLIENT: Client Simulation via Conversational Trajectory Modeling for Trainee Practice and Model Evaluation in Mental Health Counseling](https://mlsanity.com/paper/2601.07312/) (2026)
- [When to Call an Apple Red: Humans Follow Introspective Rules, VLMs Don't](https://mlsanity.com/paper/2604.06422/) (2026)
- [CyberJurors: A Multi-Agent Simulation Task for E-Commerce Disputes Verdict](https://mlsanity.com/paper/2605.28369/) (2026)
- [PL-CA: A Parametric Legal Case Augmentation Framework](https://mlsanity.com/paper/2509.06356/) (2025)
- [EduDial: Constructing a Large-scale Multi-turn Teacher-Student Dialogue Corpus](https://mlsanity.com/paper/2510.12899/) (2025)
- [PyFi: Toward Pyramid-like Financial Image Understanding for VLMs via Adversarial Agents](https://mlsanity.com/paper/2512.14735/) (2025)
- [DLawBench: Evaluating LLMs Through Multi-Turn Legal Consultation](https://mlsanity.com/paper/2606.13931/) (2026)
- [CatalogAgent: A Supervisor-mediated Self-Learning System Enabling Context Engineering for GenAI Models](https://mlsanity.com/paper/2607.14396/) (2026)
- [LiveSim: Simulating Environment-Shaped Users in Multi-Agent Live-Stream Ecosystems](https://mlsanity.com/paper/2608.26849/) (2026)
- [When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors](https://mlsanity.com/paper/2609.09887/) (2026)
- [ParaAgent: Reinforcing Parallel Acting in Open-World Tool Environments](https://mlsanity.com/paper/2609.33618/) (2026)
- [LawCompass: Navigating from Legal QA to Multi-Agent Deep Research with Grounded Evidence](https://mlsanity.com/paper/2610.01027/) (2026)

## Abstract (arXiv)

Large Language Models (LLMs) have significantly advanced legal intelligence, but the scarcity of scenario data impedes the progress toward interactive legal scenarios. This paper introduces a Multi-agent Legal Simulation Driver (MASER) to scalably generate synthetic data by simulating interactive legal scenarios. Leveraging real-legal case sources, MASER ensures the consistency of legal attributes between participants and introduces a supervisory mechanism to align participants' characters and behaviors as well as addressing distractions. A Multi-stage Interactive Legal Evaluation (MILE) benchmark is further constructed to evaluate LLMs' performance in dynamic legal scenarios. Extensive experiments confirm the effectiveness of our framework.