When RAG Fails to Equalize: Geo-bias in Factual Question Answering over Public Companies

Abhinav Havaldar, Enrico Santus

Retrieval-augmented generation (RAG) is widely assumed to mitigate factual errors in large language models (LLMs), but it remains unclear whether retrieval uniformly compensates fo…