Summary of Law: Legal Agentic Workflows For Custody and Fund Services Contracts, by William Watson et al.
LAW: Legal Agentic Workflows for Custody and Fund Services Contracts
by William Watson, Nicole Cho, Nishan Srishankar, Zhen Zeng, Lucas Cecchi, Daniel Scott, Suchetha Siddagangappa, Rachneet Kaur, Tucker Balch, Manuela Veloso
First submitted to arxiv on: 15 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The abstract presents a novel approach called LAW (Legal Agentic Workflows) that addresses the challenges of processing unstructured legal contracts in the custody and fund services domain. Large Language Models (LLMs) struggle to ingest these contracts due to lengthy text streams, limited context windows, and complex legal jargon. To overcome these limitations, LAW features a modular design that integrates multiple specialized agents and tools to respond to user queries. Experimental results show that LAW outperforms the baseline by 92.9% points in complex tasks such as calculating contract termination dates. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary LAW is a new way to help computers understand legal contracts. These contracts have lots of text, complicated language, and tricky rules. Computers have trouble making sense of them. The team behind LAW created a special system that uses many different tools and agents to understand the contracts. This helps computers do tasks like figuring out when a contract ends. LAW is better at this than other systems and can even save money by using tools that don’t need to be customized. |
