ContractScrub: A benchmark for final review of legal contracts
Legal work, with its heavy reliance on processing large amounts of text, is often considered one of the domains most exposed to the use of LLMs. Contract ``scrubbing,'' the final review of transactional agreements for errors and inconsistencies, is a particularly suitable task for automation, because it is routine, painstaking work requiring detailed attention to long documents. Scrubbing also seems to align naturally with the general capabilities expected of frontier LLMs around long-context reasoning, consistency checking, and named entity recognition (NER). Despite the economic value and po
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- PossiblePossibly related (embedding) · 50%Cutting RAG inference costs 6x starts with deciding what never reaches the LLM →
- PossiblePossibly related (embedding) · 50%Improve contract search accuracy with auto-generated filters in Amazon Bedrock →
- PossiblePossibly related (embedding) · 49%Team-lead told me to Ai-ify the contract review process and i discovered this when i got in there →
- FuzzySimilar title/name (fuzzy) · 59%jeinlee1991/chinese-llm-benchmark →
“Fuzzy title match (0.73): “ContractScrub: A benchmark for final review of legal contrac” ≈ “jeinlee1991/chinese-llm-benchmark””
- FuzzySimilar title/name (fuzzy) · 59%tirth8205/code-review-graph →
“Fuzzy title match (0.73): “ContractScrub: A benchmark for final review of legal contrac” ≈ “tirth8205/code-review-graph””
- LinkedLinked via arxiv author · 85%Yejin Bang →
“ContractScrub: A benchmark for final review of legal contracts”
- LinkedLinked via arxiv author · 85%Kirsty Fielding →
“ContractScrub: A benchmark for final review of legal contracts”
- LinkedLinked via arxiv author · 85%Brandan Oliver →
“ContractScrub: A benchmark for final review of legal contracts”