PAKTON: A Multi-Agent Framework for Question Answering in Long Legal Agreements
This addresses the challenge of making contract analysis more accessible and privacy-preserving for non-experts, though it appears incremental as it builds on existing multi-agent and RAG techniques.
The paper tackles the problem of automating contract review for legal agreements by introducing PAKTON, a multi-agent framework that improves predictive accuracy, retrieval performance, explainability, completeness, and grounded justifications compared to existing models.
Contract review is a complex and time-intensive task that typically demands specialized legal expertise, rendering it largely inaccessible to non-experts. Moreover, legal interpretation is rarely straightforward-ambiguity is pervasive, and judgments often hinge on subjective assessments. Compounding these challenges, contracts are usually confidential, restricting their use with proprietary models and necessitating reliance on open-source alternatives. To address these challenges, we introduce PAKTON: a fully open-source, end-to-end, multi-agent framework with plug-and-play capabilities. PAKTON is designed to handle the complexities of contract analysis through collaborative agent workflows and a novel retrieval-augmented generation (RAG) component, enabling automated legal document review that is more accessible, adaptable, and privacy-preserving. Experiments demonstrate that PAKTON outperforms both general-purpose and pretrained models in predictive accuracy, retrieval performance, explainability, completeness, and grounded justifications as evaluated through a human study and validated with automated metrics.