Real user queries often look different from the clean, concise ones in academic benchmarks - ambiguity, full of typos, and much less readable. We show that even strong RAG systems quickly break under these conditions. Awesome project led by @neelbhandari.bsky.social and @tianyucao.bsky.social!!

These days RAG systems have gotten popular for boosting LLMs—but they're brittle💔. Minor shifts in phrasing (✍️ style, politeness, typos) can wreck the pipeline. Even advanced components don’t fix the issue. Check out this extensive eval by @neelbhandari.bsky.social and @tianyucao.bsky.social!

1/🚨 𝗡𝗲𝘄 𝗽𝗮𝗽𝗲𝗿 𝗮𝗹𝗲𝗿𝘁 🚨 RAG systems excel on academic benchmarks - but are they robust to variations in linguistic style? We find RAG systems are brittle. Small shifts in phrasing trigger cascading errors, driven by the complexity of the RAG pipeline 🧵

it's so important to make time for yourself, rest, treat yourself gently and with kind words. you, not me, I have to run myself ragged until I collapse in a pile of exhausted self-hatred but you should definitely self care.