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Paper Citation Record · LEDGER

On the Expressive Power of Self-Attention Matrices

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2106.03764.

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

pith.paper-citation-record.v1
2106.03764 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:49:15.637004Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:07:09.244510Z

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 e16670d8-40d1-4f20-8134-227a63d0a8e5 · inbound

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models cites this paper.

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models On the Expressive Power of Self-Attention Matrices

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-17T18:00:50.487379Z

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=2026-05-17T18:00:50.053377Z digest=sha256:e59d25aa6de48b327d9bbd8c860b60f3e29aafabfd25cbd7bcef7bf9993cd70a

Observation e438c3b7-fe55-4df0-8a73-d28372071b9c · inbound

A Theory for Compressibility of Graph Transformers for Transductive Learning cites this paper.

A Theory for Compressibility of Graph Transformers for Transductive Learning On the Expressive Power of Self-Attention Matrices

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T17:05:46.778144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T17:05:46.778144Z digest=sha256:1ff4f22fbb0a79a380b959ed9d0bdcc11e796480bf48cde3e8bf7c97427210e9

Observation 41d3ef9c-2de4-41fd-9c7d-7c548ac28b21 · inbound

Transformers Meet In-Context Learning: A Universal Approximation Theory cites this paper.

Transformers Meet In-Context Learning: A Universal Approximation Theory On the Expressive Power of Self-Attention Matrices

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T10:33:40.270823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:33:40.270823Z digest=sha256:de8cb008de419bb9c485e0eb1b6d661935d00cd3b35cd418f615c2f02e4add1e

Observation dae4161d-c791-40f6-9e6c-693df28b69e8 · inbound

Sample Complexity and Representation Ability of Test-time Scaling Paradigms cites this paper.

Sample Complexity and Representation Ability of Test-time Scaling Paradigms On the Expressive Power of Self-Attention Matrices

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T10:35:36.139688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:35:36.139688Z digest=sha256:433427bc4b51f9af5df26ba00fdbb04ecb99b7169f34286a751d2af8e7fc13d3

Observation a19f856e-914a-4962-bedf-4c7694a05efa · inbound

A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization cites this paper.

A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization On the Expressive Power of Self-Attention Matrices

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T06:10:19.335874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:10:19.335874Z digest=sha256:b976e830851a473b134b8e55a268283e7b7794b32389d409a7ea2b5eea256025

Observation b1cb341f-a7b4-484e-9edb-60d51ab010aa · inbound

Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation cites this paper.

Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation On the Expressive Power of Self-Attention Matrices

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T15:49:15.637004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:49:15.637004Z digest=sha256:9b85d38039731a76b91f2c15b1a6c91b53cd0dc9f2a2a30db3f743dba9fe9b3f

Observation da8a465b-761c-47b6-bc01-42d036604257 · inbound

Nexusformer: Nonlinear Attention Expansion for Stable and Inheritable Transformer Scaling cites this paper.

Nexusformer: Nonlinear Attention Expansion for Stable and Inheritable Transformer Scaling On the Expressive Power of Self-Attention Matrices

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:41:04.835429Z

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=2026-05-10T03:14:08.351368Z digest=sha256:bcd131efcdfc48cd623fd15c530777120864562d1e918e55287b39ff0525511a

Observation 1ed87fb8-3af5-4121-bb4b-e6d5813b42fa · inbound

Analogies between Transformer Layers and Power Method cites this paper.

Analogies between Transformer Layers and Power Method On the Expressive Power of Self-Attention Matrices

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:04:01.118155Z

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=2026-06-29T22:59:25.289762Z digest=sha256:9d0653cfc065f24ace5ef150fe13048c1c238917425d36f75b2503c6d0249db8

Observation 799df850-cbc4-4436-8b2d-93ae6a3b9a51 · inbound

Looped Transformers with Layer Normalization Provably Learn the Power Method cites this paper.

Looped Transformers with Layer Normalization Provably Learn the Power Method On the Expressive Power of Self-Attention Matrices

Reference 69

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T19:22:35.265340Z

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=2026-06-28T19:03:51.212121Z digest=sha256:ac5bbef8eae6508975bd7981b5c6cf7f3cf56bb42840067e6d68b7a80aacc42f

Observation e8c213b2-ba2d-4643-82aa-08986371a909 · inbound

UNIVID: Unified Vision-Language Model for Video Moderation cites this paper.

UNIVID: Unified Vision-Language Model for Video Moderation On the Expressive Power of Self-Attention Matrices

Reference 67

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:07:09.246168Z

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=2026-06-27T22:56:26.674841Z digest=sha256:81ac9dd0d4553c0d618f550725cc406b9b8ed9af873d9555b4d2f0d49e1002d9