Paper Citation Record · LEDGER

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity

As of 11 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.20393.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.20393 v2

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T10:03:03.971313Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

verified exact0
verified fuzzy0
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e4d4465-d0f5-4793-a7ff-549eaca2175c · outbound

This paper cites Proceedings of the 43rd International.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Proceedings of the 43rd International

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:01.700174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91388833-a0b9-4e28-94a1-03ac7448ec09 · outbound

This paper cites Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages =

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:01.868431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78278160-bc49-4e0f-bba4-8510685a8992 · outbound

This paper cites Proceedings of the 31st.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Proceedings of the 31st

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:01.989991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58c55e75-26a4-44e5-8d78-59fbbac788bb · outbound

This paper cites MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:02.129130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e21b64fe-e7d1-47ae-8471-4d983116b108 · outbound

This paper cites Multi-Vector Embeddings are Provably More Expressive than Single Vector Embeddings.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Multi-Vector Embeddings are Provably More Expressive than Single Vector Embeddings

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:02.277559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 825f8c3b-427a-4863-8e0b-e9224d0ec8de · outbound

This paper cites Sherstov , title =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Sherstov , title =

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:02.405378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac54be5d-4f53-41f8-80b6-2b29c83e4fe5 · outbound

This paper cites Sherstov , title =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Sherstov , title =

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:02.601751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9528a5e-ce28-4165-aed2-efdc602e6376 · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Advances in Neural Information Processing Systems , volume =

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:02.720790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62517dad-40d1-47cf-bd60-ca1644bda85f · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity The Fourteenth International Conference on Learning Representations , year =

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:02.862887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3a78a9e-b477-4c7a-a988-b436ab12bba6 · outbound

This paper cites arXiv preprint arXiv:2603.29519 , year =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity arXiv preprint arXiv:2603.29519 , year =

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:02.975042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b43ba074-8c1a-4c1e-967b-47fb271903b6 · outbound

This paper cites arXiv preprint arXiv:2512.12458 , year =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity arXiv preprint arXiv:2512.12458 , year =

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.080564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f154434-036b-4cfc-a60c-d31dde233f6c · outbound

This paper cites Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages =

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.178830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70b28e84-eb34-4936-bd1a-251dfd0f96de · outbound

This paper cites Introducing Neural Bag of Whole-Words with.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Introducing Neural Bag of Whole-Words with

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.298788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bb6ad98-8c9e-4be3-b3cb-9dfa06a15834 · outbound

This paper cites Multi-Vector Retrieval as Sparse Alignment.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Multi-Vector Retrieval as Sparse Alignment

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.382419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a9b0ef6-67d1-407c-b0c8-7ba9f795b231 · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Advances in Neural Information Processing Systems , volume =

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.428354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92c74278-445f-46a6-8db3-db5e67c6e73e · outbound

This paper cites Advances in Information Retrieval , series =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Advances in Information Retrieval , series =

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.510613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af1fc51d-bdff-41bc-a945-a4d1f0278320 · outbound

This paper cites Proceedings of the 48th International.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Proceedings of the 48th International

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.631260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47164d84-ee22-4432-90f1-592521cd9d68 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , pages =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity The Thirteenth International Conference on Learning Representations , pages =

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.757186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89f82564-7a9c-4ab3-b1d6-d78fa334d840 · outbound

This paper cites Approximate Algorithms for Chamfer Distance Under Translation.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Approximate Algorithms for Chamfer Distance Under Translation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.841052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e7c6f57-027b-4727-9719-bc137d66b7f5 · outbound

This paper cites Jiang and Peter Kiss and Eva Szilagyi and Qiaoyuan Yang , title =.

Near-Optimal Dimension Lower Bounds for Single-Vector Embeddings of Maximum Inner Product Similarity Jiang and Peter Kiss and Eva Szilagyi and Qiaoyuan Yang , title =

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T10:03:03.971313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.