A legal team's discovery of a hallucinated clause number in an AI-generated contract summary led to the development of a multi-layered verification system. Initially, a script flagged clause references not found in the source document. This was followed by implementing strict JSON schema output and a hybrid verification process combining deterministic phrase matching and embedding similarity to ensure factual accuracy. The system also tracks output consistency across different generation runs to identify ambiguous results that require human review. AI
IMPACT Highlights the critical need for robust verification systems to prevent AI-generated factual errors in sensitive applications like legal contracts.
RANK_REASON The item describes the development of a specific tool to address AI hallucinations, rather than a new model release or significant industry event.
- Clause 23.7
- constrained decoding
- embedding similarity
- grammar constraints
- json-schema
- source_contract_v12.pdf
- token masks
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
