Simulating Dispute Mediation with LLM-Based Agents for Legal Research
On the map: LLM agents and tool use → Social simulation and multi-agent debate
Abstract (arXiv)
Legal dispute mediation plays a crucial role in resolving civil disputes, yet its empirical study is limited by privacy constraints and complex multivariate interactions. To address this limitation, we present AgentMediation, the first LLM-based agent framework for simulating dispute mediation. It simulates realistic mediation processes grounded in real-world disputes and enables controlled experimentation on key variables such as disputant strategies, dispute causes, and mediator expertise. Our empirical analysis reveals patterns consistent with sociological theories, including Group Polarization and Surface-level Consensus. As a comprehensive and extensible platform, AgentMediation paves the way for deeper integration of social science and AI in legal research.
Key facts. Cited by 7 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 10 of its 27 references that are in the map. First posted on arXiv 8 Sep 2025.
Builds on
10 of 27 references.
Closest ancestors · 3
Same direction, newest first
- 2024AgentsCourt: Building Judicial Decision-Making Agents with Court Debate Simulation and Legal Knowledge Augmentation5 Mar
- 2023War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars28 Nov
- 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr
Other references · 7
- 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
- 2024LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methodscited by 465
- 2024Emergent social conventions and collective bias in LLM populationscited by 123
- 2024AgentReview: Exploring Peer Review Dynamics with LLM Agentscited by 93
- 2021CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systemscited by 62
- 2024Robots in the Middle: Evaluating LLMs in Dispute Resolutioncited by 14
- 2025KODIS: A Multicultural Dispute Resolution Dialogue Corpuscited by 9
Built on by
Citing papers per year: 2025: 1; 2026: 6.
7 papers.
- 2026LLM Agents in Law: Taxonomy, Applications, and Challengescited by 5
- 2025ProMediate: A Socio-cognitive framework for evaluating proactive agents in multi-party negotiationcited by 3
- 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathycited by 0
- 2026Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgmentscited by 0
- 2026SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variationscited by 0
- 2026Civil Court Simulation with Large Language Modelscited by 0
- 2026ProMediConv: Benchmarking Proactive Conversational Agents in Legal Dispute Mediationcited by 0
- 2026ProMediConv: Benchmarking Proactive Conversational Agents in Legal Dispute Mediation10 Sep 2026
- 2026Civil Court Simulation with Large Language Models8 Jun 2026
- 2026SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations4 Jun 2026
- 2026Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgments5 May 2026
- 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathy12 Apr 2026
- 2026LLM Agents in Law: Taxonomy, Applications, and Challenges8 Jan 2026
- 2025ProMediate: A Socio-cognitive framework for evaluating proactive agents in multi-party negotiation29 Oct 2025
Similar, not cited
Close in wording, no citation either way
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- 2024Agents on the Bench: Large Language Model Based Multi Agent Framework for Trustworthy Digital Justice
- 2024LegalAgentBench: Evaluating LLM Agents in Legal Domain
- 2026L-MAD: A Systematic Evaluation of Multi-Agent Debate Structures in Legal Reasoning
- 2026Parthenon Law: A Self-Evolving Legal-Agent Framework
- 2024Simulating The U.S. Senate: An LLM-Driven Agent Approach to Modeling Legislative Behavior and Bipartisanship