Papers
arxiv:2603.22587

flexvec: SQL Vector Retrieval with Programmatic Embedding Modulation

Published on Mar 23
Authors:

Abstract

Programmatic Embedding Modulation enables efficient retrieval operations by exposing embedding matrices and score arrays as programmable surfaces for arithmetic operations within a SQL interface.

AI-generated summary

As AI agents become the primary consumers of retrieval APIs, there is an opportunity to expose more of the retrieval pipeline to the caller. flexvec is a retrieval kernel that exposes the embedding matrix and score array as a programmable surface, allowing arithmetic operations on both before selection. We refer to composing operations on this surface at query time as Programmatic Embedding Modulation (PEM). This paper describes a set of such operations and integrates them into a SQL interface via a query materializer that facilitates composable query primitives. On a production corpus of 240,000 chunks, three composed modulations execute in 19 ms end-to-end on a desktop CPU without approximate indexing. At one million chunks, the same operations execute in 82 ms.

Community

Sign up or log in to comment

Get this paper in your agent:

hf papers read 2603.22587
Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2603.22587 in a model README.md to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2603.22587 in a dataset README.md to link it from this page.

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2603.22587 in a Space README.md to link it from this page.

Collections including this paper 1