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Paper Citation Record · LEDGER

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization

As of 18 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2501.13992.

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

pith.paper-citation-record.v1
2501.13992 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:55:41.968724Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

19 of 19 outbound references displayed

  • verified exact0
  • verified fuzzy10
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f98d6ac0-1049-4810-b628-1e5755138678 · outbound

This paper cites Estimating local intrinsic dimensionality.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Estimating local intrinsic dimensionality

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.647705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.852245Z digest=sha256:f708e72315d78c7e765f6d09ca00bd6dd9e8851c22a3441dae04f8a40d709a22

Observation 97617bc2-3f9b-4a89-9bfd-1cefb160d43b · outbound

This paper cites Babenko and V.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Babenko and V

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.628741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.858522Z digest=sha256:0ac92d94e922714e6a7ca7e9c8f5194ba472a6597d05d45d1037bd39fe263fe2

Observation 799c39ce-8491-4442-8988-75580cb5dfc7 · outbound

This paper cites Learning to route in similarity graphs.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Learning to route in similarity graphs

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.605975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.865357Z digest=sha256:52ca3317b700e93d1db6e13c9ba4e8e8ed9691f4cce78f8e251a04957469e29a

Observation 0c1d9277-6cc5-4e6e-89e2-04b04dfadc03 · outbound

This paper cites Computational enhancements of hnsw targeted to very large datasets.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Computational enhancements of hnsw targeted to very large datasets

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.582866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.872917Z digest=sha256:795a170e3a7cf437b48be09cd5c1119b248a49a77b3187b1cce95effd4a6c1b7

Observation 63932c13-f262-442b-9890-0cfec6b8988c · outbound

This paper cites an unresolved cited work.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:41.879848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:55:41.879848Z digest=sha256:9e91e6eced67057393be159cce1344d8c8f3a8a6898e50c36b3946f6a3023b45

Observation e06d7e38-17b9-4de7-a78f-c84c34ff4448 · outbound

This paper cites Hand, Heikki Mannila, and Padhraic Smyth.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Hand, Heikki Mannila, and Padhraic Smyth

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.562464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.885754Z digest=sha256:c3f5c6b78b7b33134716de5faeb013dd235988a964c3c108d14112488b672aa5

Observation c738eca8-6297-41e5-921a-6ee27968d504 · outbound

This paper cites Houle, E.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Houle, E

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.542163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.891906Z digest=sha256:b6937b938be0c302476ba48a4f70bf96e5cee8cb24b2ccff20c761f51fc5a740

Observation d1d54716-6120-4fe9-aa1b-317f360aa717 · outbound

This paper cites Billion-scale similarity search with gpus.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Billion-scale similarity search with gpus

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.522789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.898656Z digest=sha256:adbd18e7c502e05a6b18402f18ff7470a42f0f1c8122448700e98d26f7ff5b62

Observation 9b02ec68-ac00-4086-9436-892747d4800f · outbound

This paper cites Jégou, M.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Jégou, M

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.502994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.905769Z digest=sha256:0c41fc01fd9b0cad1608fc4b8ba118afad7bc418a05939ad501b53a3ad3d290d

Observation 36ca087b-7238-45af-bb9d-870edf0e9416 · outbound

This paper cites an unresolved cited work.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:55:42.484095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.911880Z digest=sha256:b876cb9856cf2b068f2c7fc1f817b43b846a91ce7c935803122fa367368e9286

Observation e73aeea9-fd91-4eb1-91e3-d5b2f74c23ce · outbound

This paper cites Graph based Nearest Neighbor Search: Promises and Failures.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Graph based Nearest Neighbor Search: Promises and Failures

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:41.918732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:55:41.918732Z digest=sha256:71e2a4e16b6eeff23eb97139180ea25efa82e745286d04c9d8cccdbadf28d725

Observation 7635843f-bbd1-4128-b6e9-9540d75b630d · outbound

This paper cites an unresolved cited work.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:41.924885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:55:41.924885Z digest=sha256:e524e441bd3a17263c879da71b118001b14d95cb1ff73060854cfffacb952372

Observation b3b40ee1-7eb2-4525-8a3b-2475b1364a4c · outbound

This paper cites Pennington, R.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Pennington, R

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.454848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.931273Z digest=sha256:73a60904f257b3285d0611ed2d599ddfde8242e48a3f153e0bd4c4d3f8916e00

Observation b2c54067-11de-4042-90e7-7edd99e33b70 · outbound

This paper cites an unresolved cited work.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-10T15:55:42.435628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.936674Z digest=sha256:a98fbc159a4f3aa770cd5e9d597c9151947d6debe012b1364995fd065ad6db01

Observation b2769ea2-e3ea-4972-bd4a-f5dbba07d990 · outbound

This paper cites Connecting compression spaces with transformer for approximate nearest neighbor search.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Connecting compression spaces with transformer for approximate nearest neighbor search

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:55:42.417561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-10T15:55:41.942274Z digest=sha256:eee7fad0df5d5fedf9d3ade8053f2cf617ac1876d612f3ed0b5075d4672c6e82

Observation 9c31cf9f-d9bd-4610-8664-14de4b56f3fa · outbound

This paper cites write newline.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization write newline

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:41.947738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:55:41.947738Z digest=sha256:0a3ab98b26684af75e34cc2d67e20d645302d470336a885cf81f3e0cec175b82

Observation cd45a546-2be2-4c3d-94f3-825bcedfdd64 · outbound

This paper cites @esa (Ref.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization @esa (Ref

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:41.954950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:55:41.954950Z digest=sha256:e3d9060911e083fa2972a2176850da7dcd603b6155c8b2c0773699f0d48925d2

Observation 156d45ec-c3bc-4056-989d-a8411fb5f24e · outbound

This paper cites an unresolved cited work.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization Unresolved cited work

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:41.962619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:55:41.962619Z digest=sha256:bc284ba96d9b88baf432ea3e9050f79ebbac88caa45fb6f9554b1f6a80c32ea4

Observation 771ab51b-904a-4fcd-9a30-0b41ee9fc3df · outbound

This paper cites _ 8 BRS> <yvݵ?gm | XW ލ Zu x;ydk 8S] =`g xm c 05 ̫FXXpyתsz4a„&//4i233 ͭުDIReeٽ>RAA /ht<կ .o߾l޼9` ]w:봴4M4)5/ |]Mv >&Ol^޷o + UW`e?v[ D k0eʔ& 6h͚3gy]AAz꥙3gG mc5e ;ɻݮ]uVm޼Y۷o[8Tj]; @8.

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization _ 8 BRS> <yvݵ?gm | XW ލ Zu x;ydk 8S] =`g xm c 05 ̫FXXpyתsz4a„&//4i233 ͭުDIReeٽ>RAA /ht<կ .o߾l޼9` ]w:봴4M4)5/ |]Mv >&Ol^޷o + UW`e?v[ D k0eʔ& 6h͚3gy]AAz꥙3gG mc5e ;ɻݮ]uVm޼Y۷o[8Tj]; @8

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T15:55:41.968724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:55:41.968724Z digest=sha256:cd99a70a671da37661f22e17a2dc1b7fec76d452cc484cc8da40aa56039ec8cb

Pith citing papers

No inbound Pith citation observations are available.