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Paper Citation Record · LEDGER

Community Recovery on Noisy Stochastic Block Models

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2505.08251.

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

pith.paper-citation-record.v1
2505.08251 v4

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:05:58.881130Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

34 of 34 outbound references displayed

  • verified exact4
  • verified fuzzy11
  • unresolved17
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 89d7776f-36c3-4754-ae50-7e15bdb7fd8e · outbound

This paper cites Community detection in graphs.

Community Recovery on Noisy Stochastic Block Models Community detection in graphs

Reference 1

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Observation 1126f11d-64e6-43a8-8c12-d9eb1832c2e3 · outbound

This paper cites Holland, Kathryn Blackmond Laskey, and Samuel Leinhardt.

Community Recovery on Noisy Stochastic Block Models Holland, Kathryn Blackmond Laskey, and Samuel Leinhardt

Reference 2

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source=pdf_text observed=2026-08-15T22:05:58.727431Z digest=sha256:ece1c18a7459efd797135a064bc273cf331de6a5af5eb99584756a50533b89b7

Observation 2cdba016-78d4-4186-9547-15baa54bfbd0 · outbound

This paper cites Latent space approaches to social network analysis.

Community Recovery on Noisy Stochastic Block Models Latent space approaches to social network analysis

Reference 3

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source=pdf_text observed=2026-08-15T22:05:58.732635Z digest=sha256:149b6415f63536d8946d5399c52dff2f0fb625af3f5ea328945c3f9dcba40336

Observation e2c3b89d-58b3-4771-b6f7-7b60408d0e47 · outbound

This paper cites Spectral clustering and the high-dimensional stochastic blockmodel.

Community Recovery on Noisy Stochastic Block Models Spectral clustering and the high-dimensional stochastic blockmodel

Reference 4

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source=pdf_text observed=2026-08-15T22:05:58.737793Z digest=sha256:d7d163c96cf9066d3b6856abfa37d1100939bbd7c396caafe2f30d6f36b10ff7

Observation 44101011-17c5-4f82-865a-f65407807b31 · outbound

This paper cites Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications.

Community Recovery on Noisy Stochastic Block Models Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications

Reference 5

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source=pdf_text observed=2026-08-15T22:05:58.742467Z digest=sha256:6d4bd0db86c29317241b170175a28a4afdbd6a53999f444521de63b487cd5e33

Observation 21aed153-01f6-4952-8c65-414adea7e7b7 · outbound

This paper cites Community detection in general stochastic block models: fundamental limits and efficient recovery algorithms.

Community Recovery on Noisy Stochastic Block Models Community detection in general stochastic block models: fundamental limits and efficient recovery algorithms

Reference 6

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.747334Z digest=sha256:58879838e9f8ca6467840f85e8eb94750b6df4cea3f4aa296adf380e64cf5d78

Observation 9194979c-9f75-4207-af52-ac850fc6e575 · outbound

This paper cites Improved graph clustering.

Community Recovery on Noisy Stochastic Block Models Improved graph clustering

Reference 7

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source=pdf_text observed=2026-08-15T22:05:58.753087Z digest=sha256:1858c9dd0055fdd9e54d601dfcbf07308c0b128c395a1e1f8e198e97b3d9edbf

Observation de4ba19d-a8b5-4bc7-800a-9d22d4f572e5 · outbound

This paper cites Achieving Exact Cluster Recovery Threshold via Semidefinite Programming.

Community Recovery on Noisy Stochastic Block Models Achieving Exact Cluster Recovery Threshold via Semidefinite Programming

Reference 8

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local_arxiv, observed 2026-08-15T22:05:59.372095Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.757627Z digest=sha256:b86f0d626b4733bc73a92ee0fe9e49e7cd5f715cac5daa65bf9b1e2c372c6fca

Observation a51f8efd-3e7a-4d41-b479-ef2d14ca1fee · outbound

This paper cites On semidefinite relaxations for the block model.

Community Recovery on Noisy Stochastic Block Models On semidefinite relaxations for the block model

Reference 9

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source=pdf_text observed=2026-08-15T22:05:58.763443Z digest=sha256:15e68bc8b0a2101fea0dc05121592b4e5e8d4a4a3ea98f4b93219990fdee9223

Observation 25635577-b8b3-46ba-9def-6932040db42c · outbound

This paper cites The Geometric Block Model.

Community Recovery on Noisy Stochastic Block Models The Geometric Block Model

Reference 10

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local_arxiv, observed 2026-08-15T22:05:59.332449Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.768488Z digest=sha256:180d886b68706f93484ad127c48f5422b5d33f4d2abbf34b16607baa9a3d15fa

Observation 136427ce-f9b6-42f3-ac0d-1ea6b52f63d0 · outbound

This paper cites V ogelstein, and Carey E.

Community Recovery on Noisy Stochastic Block Models V ogelstein, and Carey E

Reference 11

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.773384Z digest=sha256:f947a5633773725cb9b9c6cc1b2cef9fdb49561dd3c4463f2f91ff5d1b80bbbf

Observation 9e87d18c-4b48-400f-9514-1ee775c022e1 · outbound

This paper cites an unresolved cited work.

Community Recovery on Noisy Stochastic Block Models Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-15T22:05:58.782896Z digest=sha256:d315b5be69c8d03cd5a66c01e8e2fb3c197158f9bcf7f69778bb0414110bf083

Observation 6b5733fc-96f5-4353-a7db-b4e27b658dc8 · outbound

This paper cites Regularized spectral clustering under the degree-corrected stochastic blockmodel.

Community Recovery on Noisy Stochastic Block Models Regularized spectral clustering under the degree-corrected stochastic blockmodel

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.787428Z digest=sha256:f24844cf2dfad3e1f2ba9a963385ad1ec95013f85ed5ee3ab739a3537fdeebf4

Observation cbf04307-2d5d-489e-9080-c2b66e84c5cf · outbound

This paper cites Attention Is All You Need.

Community Recovery on Noisy Stochastic Block Models Attention Is All You Need

Reference 14

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source=pdf_text observed=2026-08-15T22:05:58.791980Z digest=sha256:01d0b464af273f17e8b644a002f59a8741c3e26619e46e9d55bb5108b53b0fef

Observation 78f9586f-2a97-4911-9dd2-c92b87099822 · outbound

This paper cites Spectral Clustering of Graphs with the Bethe Hessian.

Community Recovery on Noisy Stochastic Block Models Spectral Clustering of Graphs with the Bethe Hessian

Reference 15

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source=pdf_text observed=2026-08-15T22:05:58.796735Z digest=sha256:9ea6aad45e85843f9f09f4385defb4d8605855e81cb66764e7e277d06bc77b6f

Observation 4ac770f9-3d55-4bd5-a033-d37708ce162e · outbound

This paper cites an unresolved cited work.

Community Recovery on Noisy Stochastic Block Models Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-15T22:05:58.801429Z digest=sha256:e7361f4e594047acc2f2bb279a287901af629ba3b36818f55cebe5131cad1df9

Observation 902fe17f-84b8-42e8-8148-c73cc547fd5f · outbound

This paper cites MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing.

Community Recovery on Noisy Stochastic Block Models MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing

Reference 17

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source=pdf_text observed=2026-08-15T22:05:58.806182Z digest=sha256:d309a75cecf5178d8ae3ffe721b852775146a8921b839c7f38989f5be8a0b613

Observation 3429eea3-352a-482c-9e49-0be7b64f2425 · outbound

This paper cites The dynamics of viral marketing.

Community Recovery on Noisy Stochastic Block Models The dynamics of viral marketing

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.811077Z digest=sha256:e5e89d2622032c5f24fdade3f94a9faa233bab2f7bc9314bc8448cae184c1689

Observation 69c55fc9-cb87-4cfd-8ff1-163e932f505e · outbound

This paper cites an unresolved cited work.

Community Recovery on Noisy Stochastic Block Models Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-15T22:05:58.815504Z digest=sha256:280607c3be2d640af76d5c9c755d6a3804b2ded39d57a4c4355539a0a47e387a

Observation 09c27ea2-ed5b-4c0c-97fd-69a6456189ce · outbound

This paper cites The rotation of eigenvectors by a perturbation.

Community Recovery on Noisy Stochastic Block Models The rotation of eigenvectors by a perturbation

Reference 20

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source=pdf_text observed=2026-08-15T22:05:58.820173Z digest=sha256:074c22a9f17eee36b7d0bdef8be14049e7c64bd89a2a31f2bd87f6656ae75088

Observation 04fe6c8c-e673-421f-9dde-0961c02de3b1 · outbound

This paper cites Reconstruction and estimation in the planted partition model.

Community Recovery on Noisy Stochastic Block Models Reconstruction and estimation in the planted partition model

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.824587Z digest=sha256:4a9b7714dca6c8e8e1eef64ff303d4e20dca928cb87ecbd158cd4714c005fed1

Observation 017784bf-4bd5-4993-8aec-3481a7a66425 · outbound

This paper cites Non-backtracking spectrum of random graphs: community detection and non-regular Ramanujan graphs.

Community Recovery on Noisy Stochastic Block Models Non-backtracking spectrum of random graphs: community detection and non-regular Ramanujan graphs

Reference 22

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local_arxiv, observed 2026-08-15T22:05:59.030193Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.829243Z digest=sha256:0ed4b3bedf771dd1e5ae0fd6b8537a41afa675c4fcb4ef741472fdf3fb56bb63

Observation a256971f-7a00-4f8c-b836-fa37e0170733 · outbound

This paper cites A unified framework for spectral clustering in sparse graphs.

Community Recovery on Noisy Stochastic Block Models A unified framework for spectral clustering in sparse graphs

Reference 23

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source=pdf_text observed=2026-08-15T22:05:58.834096Z digest=sha256:f3757e26965904a2257e3bf02bc19ac8534fb0f19db9a8085f218653e6967754

Observation b4f9d076-4ea6-4556-a100-7e996a85f551 · outbound

This paper cites Belief propagation, robust reconstruction and optimal recovery of block models.

Community Recovery on Noisy Stochastic Block Models Belief propagation, robust reconstruction and optimal recovery of block models

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:05:58.838669Z digest=sha256:35369c0f8a1c4f108fcbf2ca7be18b295bdbc272a757d1871d91ad6da00374b0

Observation 40f3d367-c0eb-4f47-8e71-1df4f6117dfd · outbound

This paper cites Community recovery in the geometric block model.

Community Recovery on Noisy Stochastic Block Models Community recovery in the geometric block model

Reference 25

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.843127Z digest=sha256:5583df7823bf2a9c83e3663616d229cd701b8f7572819d59e281b3197b4d981e

Observation 7bb9577d-09f4-4994-a26d-50c1d676ab59 · outbound

This paper cites For every unordered edgee ={i,j} set Ye = fWij− EfWij eie⊤ j +eje⊤ i , soE =P eYe and EYe = 0.4 Independent edges give independent matrices{Ye}.

Community Recovery on Noisy Stochastic Block Models For every unordered edgee ={i,j} set Ye = fWij− EfWij eie⊤ j +eje⊤ i , soE =P eYe and EYe = 0.4 Independent edges give independent matrices{Ye}

Reference 27

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.848529Z digest=sha256:5a0b023fba457d71c37483359d528fb2edd062140613f0fc7846ff0da599c297

Observation fca7f9e9-98e5-4145-ad5d-c6ae457c0f90 · outbound

This paper cites Letwin/out =pin/out exp(ρin/out/ √ d) = Θ (logn)/n.

Community Recovery on Noisy Stochastic Block Models Letwin/out =pin/out exp(ρin/out/ √ d) = Θ (logn)/n

Reference 28

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.853543Z digest=sha256:cb54b5f5dd2e9acb73491a31a010dde6f0abcd932db330151e8a1e49dbcdfec6

Observation aee7eedc-4f90-48d6-afde-41a55fca6441 · outbound

This paper cites DefineV =P e E[Y 2 e ].

Community Recovery on Noisy Stochastic Block Models DefineV =P e E[Y 2 e ]

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.858067Z digest=sha256:e0ca41166b88e6d33cf0d73bce7a9df1003b6ea84a1d1601a40e075d8a9e6003

Observation ab4d197b-6623-43ac-9b9d-76119228e881 · outbound

This paper cites Tropp’s matrix Bernstein inequality [19] gives for any t> 0 Pr ∥E∥2≥t ≤ 2n exp − t2/2 σ2+Lt/3.

Community Recovery on Noisy Stochastic Block Models Tropp’s matrix Bernstein inequality [19] gives for any t> 0 Pr ∥E∥2≥t ≤ 2n exp − t2/2 σ2+Lt/3

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.862225Z digest=sha256:e93b8b314d1573c9d07f253e5e97300c460ce70b6ed25c9f1625949e173c0644

Observation 6518f3dc-ed38-42bf-8a21-5d645f1b9161 · outbound

This paper cites With probability at least 1−O(n−2),∥E∥2≤κ√logn, i.e.∥E∥2 =O(√logn) as claimed.

Community Recovery on Noisy Stochastic Block Models With probability at least 1−O(n−2),∥E∥2≤κ√logn, i.e.∥E∥2 =O(√logn) as claimed

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.866926Z digest=sha256:eea41a34505b3a62b6c61f777a4be4d3adde6fe1f35edacb95e741190e12e976

Observation 9307ac70-ddc2-4ae5-bd32-f3c920e66ddf · outbound

This paper cites BecauseS is symmetric,λ3(S) = 0 andγ =λ2(S)−λ3(S)> 0.

Community Recovery on Noisy Stochastic Block Models BecauseS is symmetric,λ3(S) = 0 andγ =λ2(S)−λ3(S)> 0

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.872210Z digest=sha256:58a2f41a8ff4bf3705367619856b399b7f45c7d21f009572a9d59f45ceea0c56

Observation e1dd9117-7642-4c2d-8be9-c29554d558ea · outbound

This paper cites Letgi =±1 be the planted labels and notev2 =g/∥g∥ with∥g∥2 =n+ +n− =n.

Community Recovery on Noisy Stochastic Block Models Letgi =±1 be the planted labels and notev2 =g/∥g∥ with∥g∥2 =n+ +n− =n

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.876683Z digest=sha256:4603fe30ea45cbc1c0cea11f8b0325dc01b7171a260f300542eb17eea545a63b

Observation ab4071f6-19a6-46d4-a100-89f468845004 · outbound

This paper cites Combining (1)–(3) we have sin ∠(ˆv,v 2)≤∥E∥2 γ =O (logn)−1/2 , #{errors} =o(n), completing the proof.

Community Recovery on Noisy Stochastic Block Models Combining (1)–(3) we have sin ∠(ˆv,v 2)≤∥E∥2 γ =O (logn)−1/2 , #{errors} =o(n), completing the proof

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T22:05:58.881130Z digest=sha256:65c1f5872723f004f07f08b6006cdc592637ecfa6efb6cbf000524eec72e6f67

Observation a604de4a-4671-4756-9362-e3e7ce24e4bf · outbound

This paper cites an unresolved cited work.

Community Recovery on Noisy Stochastic Block Models Unresolved cited work

Reference 2021

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:05:58.778266Z digest=sha256:5f95a510d33fc7a0a29c28016d9e71b5d8c2f3ae3ac87db88da0be3a2719a821

Pith citing papers

No inbound Pith citation observations are available.