MIRA: A Bilingual Benchmark for Medical Information Response Audit

MIRA is a bilingual benchmark that evaluates whether large language models (LLMs) provide consistent medical information across different user phrasings, languages, and health literacy levels. It contains 4,320 prompts derived from 60 medically reviewed low‑risk health questions and reveals that models tend to omit key information and offer fewer concrete next steps when responding to low health‑literacy signals, a phenomenon termed Differential Information Dilution (DID). A knowledge‑guided mitigation prompt can reduce this dilution for most models, notably improving Claude and Qwen.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

• llms
• benchmarks
• safety