Cartographer is a small, fast cross-encoder that scores how well a shopping query matches a product. It takes a `(query, product)` pair and returns a single relevance score for reranking a candidate list. It is a drop-in upgrade for the general-purpose reranker it is built on: **same size, same speed, measurably better on product search.** It was fine-tuned from `cross-encoder/ms-marco-MiniLM-L-6-v2` on Amazon's public **Shopping Queries Dataset (ESCI)**. The base model was trained on web-search passages; product listings are not web text, so a domain-tuned model of the **same 22.7M-parameter footprint** does meaningfully better. Evaluated on the held-out ESCI test split (US / English): **8,956 queries, 181,701 (query, product) pairs.** Both models scored at `max_length=256`, identical settings : the comparison is apples-to-apples. The headline metric is nDCG (graded relevance), which is what the E/S/C/I labels are for.

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