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add cross-links from search and vectors docs to multi-rep tutorial

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- hybrid-queries: see-also link at end of grouping section
- vectors: clarify MaxSim returns one combined score and point to named vectors + tutorial
- text-search: BM25 short-field calibration note plus BM25F workaround pointer

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Dylan Couzon
2026-05-05 19:10:24 -04:00
co-authored by Claude Opus 4.7
parent 120895c75d
commit bb877b23f7
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qdrant-landing/content/documentation/manage-data/vectors.md
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@@ -121,6 +121,8 @@ There are two scenarios where multivectors are useful:
* **Late interaction embeddings** - Some text embedding models can output multiple vectors for a single text.
For example, a family of models such as ColBERT output a relatively small vector for each token in the text.
MaxSim returns a single combined score per point, not per subvector. For per-representation control across title, summary, and chunk embeddings, see [Named Vectors](#named-vectors) and the [Multi-Representation Search tutorial](/documentation/tutorials-search-engineering/multi-representation-search/). The [multivectors course](/course/multi-vector-search/) covers limitations at scale.
In order to use multivectors, we need to specify a function that will be used to compare between matrices of vectors
Currently, Qdrant supports `max_sim` function, which is defined as a sum of maximum similarities between each pair of vectors in the matrices.