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Paper Citation Record · LEDGER

Large Memory Layers with Product Keys

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1907.05242.

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

pith.paper-citation-record.v1
1907.05242 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:49:54.684836Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T12:46:14.651177Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a71cf3da-5ca0-4da7-b52f-c5cc2ea62fdf · inbound

CTRL: A Conditional Transformer Language Model for Controllable Generation cites this paper.

CTRL: A Conditional Transformer Language Model for Controllable Generation Large Memory Layers with Product Keys

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T06:14:02.625560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-17T06:14:02.423030Z digest=sha256:ff78664da67e27ee89ab703b09b2d97df391aba3243d3e13ace90df104aaab77

Observation 644621a4-f508-4b4d-a43a-cc12ee79f7fb · inbound

Compressive Transformers for Long-Range Sequence Modelling cites this paper.

Compressive Transformers for Long-Range Sequence Modelling Large Memory Layers with Product Keys

Reference 135

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:46:16.647894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-18T10:46:16.373197Z digest=sha256:c5a67721280cc8b78bf2fdead147210e91dfe6ce4852d476d1b535f464d39b9d

Observation da0ae785-abda-4f63-bbf1-0382038b1e15 · inbound

Reformer: The Efficient Transformer cites this paper.

Reformer: The Efficient Transformer Large Memory Layers with Product Keys

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:22:03.236360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-13T07:22:03.169913Z digest=sha256:522c3ad3b7393b1d933e905c109ec01aabfc9e8913e4a4282052608769166c50

Observation b2a2080b-3db1-4d6c-bf29-cf5102d0d924 · inbound

Memory Layers at Scale cites this paper.

Memory Layers at Scale Large Memory Layers with Product Keys

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T16:49:54.684836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T16:49:54.684836Z digest=sha256:efdf7edc5d98e09e1f95f01e2ab392b09141d4ee0fd0fb2828543f1b3a56f548

Observation bd988cdb-6b0e-45fd-9bcf-08ccd2c47440 · inbound

Do Value Vectors in Deep Layers Need Context from the Residual Stream? cites this paper.

Do Value Vectors in Deep Layers Need Context from the Residual Stream? Large Memory Layers with Product Keys

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-07-01T23:16:23.422503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-28T14:35:48.292081Z digest=sha256:1498f4f9ca283dc62cc4ce1c0bac760a2bb99a4b88557e54a39d8eaa4bec603f

Observation 336c730e-5808-410c-bc2b-d51f2534f8d1 · inbound

Do Value Vectors in Deep Layers Need Context from the Residual Stream? cites this paper.

Do Value Vectors in Deep Layers Need Context from the Residual Stream? Large Memory Layers with Product Keys

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-02T12:41:21.309541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:41:21.309541Z digest=sha256:cd21edfe7126dff56bab198abd9b364923a33c1e0be6e37b4c5a2bbc53b76769

Observation a4576ee3-db44-4117-b581-65a1dafb7c37 · inbound

Sparsely gated tiny linear experts cites this paper.

Sparsely gated tiny linear experts Large Memory Layers with Product Keys

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:17:09.301810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T22:49:49.299925Z digest=sha256:8bb5a1018dc2a6c004d70b0482afdce0196f8bbf02a09c9d2e031b4ed1f7f969

Observation 2d5446d1-674f-4e69-9153-9303af78bb5b · inbound

Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity cites this paper.

Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity Large Memory Layers with Product Keys

Reference 99

Resolution
metadata mismatch
local_arxiv, observed 2026-07-09T12:46:14.653548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-07-09T12:40:09.036905Z digest=sha256:59abe526967f15a54185e3a8d94d25f69bc555b5e6e646c60e3ff14d02aa28d5

Observation 35162da6-2bab-4646-b1b4-0ef5f375c81c · inbound

Remembering Distinct Items, Not Tokens: A Learnable Dirichlet-Process Cache Between State-Space Models and Attention cites this paper.

Remembering Distinct Items, Not Tokens: A Learnable Dirichlet-Process Cache Between State-Space Models and Attention Large Memory Layers with Product Keys

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-14T14:50:03.831572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T14:50:03.831572Z digest=sha256:b230179d6a96b0b48a8e5e1b67d1ec61ce6d7924dadf51aa0e35826257eded47