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Paper Citation Record · LEDGER

The Routing and Filtering Structure of Attention

As of 16 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2605.18826.

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

pith.paper-citation-record.v1
2605.18826 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-20T22:04:15.518405Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T01:22:42.362833Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-11T01:27:45.987053Z

Reference resolution

28 of 28 outbound references displayed

  • verified exact9
  • verified fuzzy16
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9d61c582-5575-4070-b416-70dd472127d0 · outbound

This paper cites Attention is all you need.

The Routing and Filtering Structure of Attention Attention is all you need

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.926190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b6a66969-09da-4c5d-abe2-55f53d2f5bcd · outbound

This paper cites Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models.

The Routing and Filtering Structure of Attention Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:09:07.685433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation fc25026a-2459-4649-b3a8-640968e02361 · outbound

This paper cites Jamba: A Hybrid Transformer-Mamba Language Model.

The Routing and Filtering Structure of Attention Jamba: A Hybrid Transformer-Mamba Language Model

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:09:07.725947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e1fae2d7-c4ea-4e00-96f4-2c0b0b29b0dd · outbound

This paper cites Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.

The Routing and Filtering Structure of Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:09:07.720892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 532fb9b7-f140-4b55-9b32-7302f87ea9c1 · outbound

This paper cites Zamba: A Compact 7B SSM Hybrid Model.

The Routing and Filtering Structure of Attention Zamba: A Compact 7B SSM Hybrid Model

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:09:07.715921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:1b9cfb1801532bb07aab4d4e3e7eeafd4bd1d54b6f0a20d0908c7755c2f82f47

Observation 8a90d796-e53b-4142-9145-615ed7564584 · outbound

This paper cites RecurrentGemma: Moving Past Transformers for Efficient Open Language Models.

The Routing and Filtering Structure of Attention RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T22:09:07.710312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation da269b65-1d00-4fb6-8094-6c471bc5ed03 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

The Routing and Filtering Structure of Attention Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:09:07.704589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 178b9683-0c2c-4e92-8972-11bcd618db49 · outbound

This paper cites Language models are unsupervised multitask learners.

The Routing and Filtering Structure of Attention Language models are unsupervised multitask learners

Reference 8

Resolution
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raw_fallback, observed 2026-05-20T22:14:06.908693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 51240789-eb95-460f-ae58-514c1054fe1e · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.

The Routing and Filtering Structure of Attention BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.947219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:6aedc31759b6cf51baa9ef6d308bc69c39e13f8aa4f0ef74d8ab4f323433d604

Observation c4f03c69-2e10-445c-84c8-0559c39513cb · outbound

This paper cites Layer Normalization.

The Routing and Filtering Structure of Attention Layer Normalization

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:09:07.700222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8a33c44e-7afb-442b-9fe3-fe8fd471ea7c · outbound

This paper cites Interpretable Physics Extraction from Data for Linear Dynamical Systems using Lie Generator Networks.

The Routing and Filtering Structure of Attention Interpretable Physics Extraction from Data for Linear Dynamical Systems using Lie Generator Networks

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:09:07.695917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation cd0f5456-ce79-4103-a863-b283459363db · outbound

This paper cites Lie Generator Networks for Nonlinear Partial Differential Equations.

The Routing and Filtering Structure of Attention Lie Generator Networks for Nonlinear Partial Differential Equations

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:09:07.690700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 437458a5-2bd4-4903-802e-b6d7b1b807f8 · outbound

This paper cites Gokaslan and V.

The Routing and Filtering Structure of Attention Gokaslan and V

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.944600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 4ea1a121-b9e1-4da1-bb35-6358c26c673f · outbound

This paper cites Pointer sentinel mixture models.

The Routing and Filtering Structure of Attention Pointer sentinel mixture models

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.942621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:35f064c50c7e2eafc9718417c74cfd15f49a8823ad0137b881ea1f3286942fc1

Observation b94d705e-2067-4c09-ba85-e422d35390b2 · outbound

This paper cites FlashAttention: Fast and memory-efficient exact attention with IO-awareness.

The Routing and Filtering Structure of Attention FlashAttention: Fast and memory-efficient exact attention with IO-awareness

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.940132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:7ef305d350270a117f97369751d19080ebdf7772cd92a56c89a09841289c3563

Observation a022f8de-411f-4729-9ec6-e57944501792 · outbound

This paper cites Transformers are RNNs: Fast autoregressive transformers with linear attention.

The Routing and Filtering Structure of Attention Transformers are RNNs: Fast autoregressive transformers with linear attention

Reference 16

Resolution
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raw_fallback, observed 2026-05-20T22:14:06.935443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:4436a4313911d35aad228f529e24225f4a9bbd4f0ede11fd5bbce76cec9bfe7e

Observation dfa321bc-56ab-409a-850b-5483c70dcb02 · outbound

This paper cites Efficiently modeling long sequences with structured state spaces.

The Routing and Filtering Structure of Attention Efficiently modeling long sequences with structured state spaces

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.930440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c514e94e-ff70-446c-935c-042f9e92a9b4 · outbound

This paper cites Gated linear attention transformers with hardware- efficient training.

The Routing and Filtering Structure of Attention Gated linear attention transformers with hardware- efficient training

Reference 18

Resolution
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raw_fallback, observed 2026-05-20T22:14:06.928209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:20dbd825fce1e658c4d6eb8d834c97d42408b2b192f4005f6ea41f0fdf057129

Observation 76ecafe3-7333-4a8b-bb2f-34481a235b2e · outbound

This paper cites Rethinking attention with Performers.

The Routing and Filtering Structure of Attention Rethinking attention with Performers

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.924218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3b6b1093-9b9b-432e-810f-1b4bc2800616 · outbound

This paper cites RWKV: Reinventing RNNs for the transformer era.

The Routing and Filtering Structure of Attention RWKV: Reinventing RNNs for the transformer era

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.910915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:b8759652214ada90f66953db290b8d65a38e6dc6f0d3fd82ab86d8b05eae299e

Observation 4a4c6822-a450-4988-9ef5-4af66e15c6a2 · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

The Routing and Filtering Structure of Attention Retentive Network: A Successor to Transformer for Large Language Models

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:09:07.730795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:10777fb954f82c985725c6e5795aa81c8cea120e89f801ea78e4e8cea4686629

Observation 59075ebd-ad7b-42c6-8658-b2724bc619d7 · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling.

The Routing and Filtering Structure of Attention Pythia: A suite for analyzing large language models across training and scaling

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.921982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:fbb9acadf26adce579a835f1a4c670745ea1cdb7857b0c6866412b372707c434

Observation a601efdc-1474-46ad-91cc-f3cac4008274 · outbound

This paper cites The cat sat on the mat and then it slowly walked to the door.

The Routing and Filtering Structure of Attention The cat sat on the mat and then it slowly walked to the door

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.932961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b0004037-9212-4cc2-915d-c82b3bf6a1bc · outbound

This paper cites an unresolved cited work.

The Routing and Filtering Structure of Attention Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-05-20T22:14:06.920037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:520a50c27707421da5bf7db16ccc1f5f5f6e9d3dce9f9d77ba5adf6df51fd591

Observation fd9a283c-ef14-4984-8bd8-372ea954407d · outbound

This paper cites an unresolved cited work.

The Routing and Filtering Structure of Attention Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-05-20T22:14:06.917473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:0010bb3b9d74aa900401628f82c7204d00ad6ec3605f0fc85ec62cafb4a153cf

Observation 91b37d2c-9255-4e83-a151-310fa761f2b5 · outbound

This paper cites She told him that the book he had lent her, which she had finally finished reading over the weekend, was one of the most thought-provoking novels she had encountered in years.

The Routing and Filtering Structure of Attention She told him that the book he had lent her, which she had finally finished reading over the weekend, was one of the most thought-provoking novels she had encountered in years

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.915495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:db6ed7e59d4b8271abae70df620579e5d3812ba97fb9dbcf0ea46a4f911ff232

Observation 55e020c0-9dc5-4f24-8711-59200bd6e616 · outbound

This paper cites The quick brown fox jumps over the lazy dog.

The Routing and Filtering Structure of Attention The quick brown fox jumps over the lazy dog

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.913006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:aea36a291e66ea303fb27e31d6e623ed1585a88b7bfe76faa3c589d33364fcd6

Observation 5afafbb1-17e1-4d0f-b379-ea73292d91ef · outbound

This paper cites Token counts reflect GPT-2 BPE tokenization.

The Routing and Filtering Structure of Attention Token counts reflect GPT-2 BPE tokenization

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T22:14:06.937973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T22:04:15.518405Z digest=sha256:7fdf44e6c192b8615e3b56b2b9bbb21c49cb3fa2ab331dbc5de81471c6b92742

Pith citing papers

Observation 9cb175b6-b972-4743-97ea-589654c9ea5a · inbound

Fingerprint, Not Blueprint: How Positional Schemes Set the Default Spectral Algebra of Attention cites this paper.

Fingerprint, Not Blueprint: How Positional Schemes Set the Default Spectral Algebra of Attention The Routing and Filtering Structure of Attention

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-07-11T01:27:46.012609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-07-11T01:22:42.362833Z digest=sha256:80e4080b2111332766c32b84c8f66e2d4fc893c662bc96bf99d117feeb0898ea