Temporal Misgrounding in Legal RAG: A Versioned-Corpus Benchmark for French Tax Law
The episode discusses a paper on temporal misgrounding in legal RAG systems, where LLMs fail to answer questions about French tax law at past dates. Testing 11 models, they found 3% accuracy from memory and 2.7% with standard RAG, but 98.3% with date-conditioned retrieval over a versioned corpus. The hosts conclude that temporal indexing is crucial for legal QA.