Paper Citation Record · LEDGER

Transformers versus the EM Algorithm in Multi-class Clustering

As of 9 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2502.06007.

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

pith.paper-citation-record.v1
2502.06007 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:13:25.912152Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T12:22:27.265973Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:16:09.612834Z

Reference resolution

41 of 41 outbound references displayed

verified exact1
verified fuzzy16
unresolved24
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 609d41dc-bc28-44e5-9c85-57f43c28f0f5 · outbound

This paper cites write newline.

Transformers versus the EM Algorithm in Multi-class Clustering write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:24.966113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9003ed7-4d61-4d32-9f02-c85e49f3f7c5 · outbound

This paper cites write newline.

Transformers versus the EM Algorithm in Multi-class Clustering write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:24.973894Z

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Unavailable: canonical work link unavailable.

Observation 42f92e7d-a146-4f3b-8a53-cf41d3be4f0c · outbound

This paper cites V., and Warmuth, M.

Transformers versus the EM Algorithm in Multi-class Clustering V., and Warmuth, M

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.836041Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 965109c9-3736-40b8-8a8e-f8ae1156ef25 · outbound

This paper cites Transformers learn to implement preconditioned gradient descent for in-context learning.

Transformers versus the EM Algorithm in Multi-class Clustering Transformers learn to implement preconditioned gradient descent for in-context learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.694937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c8dababd-b180-4da9-bbf5-b4f196e0765a · outbound

This paper cites What learning algorithm is in-context learning? Investigations with linear models.

Transformers versus the EM Algorithm in Multi-class Clustering What learning algorithm is in-context learning? Investigations with linear models

Reference 5

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Observation 5bddbedd-a814-409c-90a9-394b78ab7bfa · outbound

This paper cites Breaking the curse of dimensionality with convex neural networks.

Transformers versus the EM Algorithm in Multi-class Clustering Breaking the curse of dimensionality with convex neural networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.672760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d309d358-62e6-44d3-ac76-6c574116d02a · outbound

This paper cites Transformers as statisticians: Provable in-context learning with in-context algorithm selection.

Transformers versus the EM Algorithm in Multi-class Clustering Transformers as statisticians: Provable in-context learning with in-context algorithm selection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.541963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8573e64e-48b6-4e42-9380-0cc163251735 · outbound

This paper cites On the Computational Power of Transformers and its Implications in Sequence Modeling.

Transformers versus the EM Algorithm in Multi-class Clustering On the Computational Power of Transformers and its Implications in Sequence Modeling

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:25.003270Z

Source-reported events for the cited work

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Observation 1468d5b3-165e-4160-9fcf-21f87fc48133 · outbound

This paper cites an unresolved cited work.

Transformers versus the EM Algorithm in Multi-class Clustering Unresolved cited work

Reference 9

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Source-reported events for the cited work

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Observation b66905c9-9f50-4e79-91d7-c9bb567967f5 · outbound

This paper cites Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality.

Transformers versus the EM Algorithm in Multi-class Clustering Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:25.061703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9831045-b21c-412c-867d-7bf1451bc2aa · outbound

This paper cites How transformers utilize multi-head attention in in-context learning? a case study on sparse linear regression.

Transformers versus the EM Algorithm in Multi-class Clustering How transformers utilize multi-head attention in in-context learning? a case study on sparse linear regression

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.447164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2fd659ec-5ad5-4404-882d-f8f2bc0922cd · outbound

This paper cites How Well Can Transformers Emulate In-context Newton's Method?.

Transformers versus the EM Algorithm in Multi-class Clustering How Well Can Transformers Emulate In-context Newton's Method?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:25.085621Z

Source-reported events for the cited work

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Observation 6ed2557f-9bf8-4aeb-9b7e-50038db5f801 · outbound

This paper cites Learning Spectral Methods by Transformers.

Transformers versus the EM Algorithm in Multi-class Clustering Learning Spectral Methods by Transformers

Reference 13

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Source-reported events for the cited work

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Observation fa12f09b-2172-4533-8849-ef380f68c8a6 · outbound

This paper cites In-Context Convergence of Transformers.

Transformers versus the EM Algorithm in Multi-class Clustering In-Context Convergence of Transformers

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:25.095912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6861c27c-5cd7-4cbd-a497-1456f05af03b · outbound

This paper cites T., Lv, J., and Peng, X.

Transformers versus the EM Algorithm in Multi-class Clustering T., Lv, J., and Peng, X

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50b37b80-7605-4848-90b7-b178edf2ed15 · outbound

This paper cites Vision transformers provably learn spatial structure.

Transformers versus the EM Algorithm in Multi-class Clustering Vision transformers provably learn spatial structure

Reference 16

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Observation 97698f0c-c291-4b94-b529-0b92a2cf621d · outbound

This paper cites J., Lee, J.

Transformers versus the EM Algorithm in Multi-class Clustering J., Lee, J

Reference 17

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Source-reported events for the cited work

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Observation 0edcaf3d-4215-44e6-86d6-1f945dbaca1d · outbound

This paper cites A simple linear time (1+/spl epsiv/)-approximation algorithm for k-means clustering in any dimensions.

Transformers versus the EM Algorithm in Multi-class Clustering A simple linear time (1+/spl epsiv/)-approximation algorithm for k-means clustering in any dimensions

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.385671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 29a67dac-380c-45cb-9299-bdf4afeed68d · outbound

This paper cites E., Papailiopoulos, D., and Oymak, S.

Transformers versus the EM Algorithm in Multi-class Clustering E., Papailiopoulos, D., and Oymak, S

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.292177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a025fb9f-c6e2-45d1-b1bc-a233b244d379 · outbound

This paper cites How do transformers learn topic structure: Towards a mechanistic understanding.

Transformers versus the EM Algorithm in Multi-class Clustering How do transformers learn topic structure: Towards a mechanistic understanding

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.152234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 18b3adb1-635d-4f59-8f27-43a5168298a9 · outbound

This paper cites Image clustering with external guidance.

Transformers versus the EM Algorithm in Multi-class Clustering Image clustering with external guidance

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1f96a89a-32b3-4b25-929e-570c1a21d040 · outbound

This paper cites M., Fan, J., and Wang, M.

Transformers versus the EM Algorithm in Multi-class Clustering M., Fan, J., and Wang, M

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:27.108960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 700c731c-2051-4cff-83c0-ff51694388c2 · outbound

This paper cites Transformers Learn Shortcuts to Automata.

Transformers versus the EM Algorithm in Multi-class Clustering Transformers Learn Shortcuts to Automata

Reference 23

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Source-reported events for the cited work

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Observation 77a016ac-eb8c-457f-8b31-826b7fccd2bc · outbound

This paper cites Least squares quantization in pcm.

Transformers versus the EM Algorithm in Multi-class Clustering Least squares quantization in pcm

Reference 24

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Source-reported events for the cited work

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Observation b7b50c47-551b-4c34-afec-1155bb59d8a5 · outbound

This paper cites Statistical and Computational Guarantees of Lloyd's Algorithm and its Variants.

Transformers versus the EM Algorithm in Multi-class Clustering Statistical and Computational Guarantees of Lloyd's Algorithm and its Variants

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:25.355845Z

Source-reported events for the cited work

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Observation 5eecf896-1c65-4a4c-bb27-be2157a0c6f3 · outbound

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Transformers versus the EM Algorithm in Multi-class Clustering Unresolved cited work

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8759ec52-ccd4-463a-a611-e0b4d3d50505 · outbound

This paper cites Deep transformation-invariant clustering.

Transformers versus the EM Algorithm in Multi-class Clustering Deep transformation-invariant clustering

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:26.830439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6b80e1e1-5bd4-4ad8-8088-cedc4cf23880 · outbound

This paper cites Scikit-learn: Machine learning in python.

Transformers versus the EM Algorithm in Multi-class Clustering Scikit-learn: Machine learning in python

Reference 28

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Source-reported events for the cited work

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Observation 5b1cba5c-e5b4-47d1-8406-c8c8dad3696b · outbound

This paper cites Attention is turing-complete.

Transformers versus the EM Algorithm in Multi-class Clustering Attention is turing-complete

Reference 29

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Observation 49cf5687-91ea-4367-9c97-d0eafedf5003 · outbound

This paper cites Maurey-Schwartz.

Transformers versus the EM Algorithm in Multi-class Clustering Maurey-Schwartz

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:26.681996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ecdbb328-c44d-4b6f-a503-a5e621aafaf9 · outbound

This paper cites LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering.

Transformers versus the EM Algorithm in Multi-class Clustering LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering

Reference 31

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Source-reported events for the cited work

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Observation 4bfb98c0-a107-4118-92b0-6f079c0e7977 · outbound

This paper cites Attention is all you need.

Transformers versus the EM Algorithm in Multi-class Clustering Attention is all you need

Reference 32

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Source-reported events for the cited work

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Observation 5f9b6948-56f6-4e8b-a9b7-85796bea3789 · outbound

This paper cites Information-theoretic methods for high-dimensional statistics.

Transformers versus the EM Algorithm in Multi-class Clustering Information-theoretic methods for high-dimensional statistics

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:13:26.595156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ce328805-e29e-4a26-a339-4448fa349653 · outbound

This paper cites Self-Attention Networks Can Process Bounded Hierarchical Languages.

Transformers versus the EM Algorithm in Multi-class Clustering Self-Attention Networks Can Process Bounded Hierarchical Languages

Reference 34

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Source-reported events for the cited work

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Observation eb409cd5-201a-4490-b5a7-bbe155cede83 · outbound

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Transformers versus the EM Algorithm in Multi-class Clustering Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-08T17:13:26.550202Z

Source-reported events for the cited work

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Observation 70a371b3-fb9d-458f-818c-9b2bd6025f81 · outbound

This paper cites Are Transformers universal approximators of sequence-to-sequence functions?.

Transformers versus the EM Algorithm in Multi-class Clustering Are Transformers universal approximators of sequence-to-sequence functions?

Reference 36

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Source-reported events for the cited work

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Observation 3f197104-1234-4984-901d-b6b61c1f982b · outbound

This paper cites and Cao, Y.

Transformers versus the EM Algorithm in Multi-class Clustering and Cao, Y

Reference 37

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Source-reported events for the cited work

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Observation c1446f92-28fc-456e-9393-cb813de2747d · outbound

This paper cites Trained Transformers Learn Linear Models In-Context.

Transformers versus the EM Algorithm in Multi-class Clustering Trained Transformers Learn Linear Models In-Context

Reference 38

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Observation d6e9c053-295d-4489-9164-c4ae2d3f5fa6 · outbound

This paper cites @esa (Ref.

Transformers versus the EM Algorithm in Multi-class Clustering @esa (Ref

Reference 39

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Source-reported events for the cited work

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Observation 461f6dd3-3456-49af-bad9-f9b903795a1f · outbound

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Transformers versus the EM Algorithm in Multi-class Clustering Unresolved cited work

Reference 40

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Source-reported events for the cited work

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Observation 4595f027-eedb-40cd-ade4-50294976d181 · outbound

This paper cites Recent efforts are devoted to understand the learning capacities of Transformers at the fundamental level.

Transformers versus the EM Algorithm in Multi-class Clustering Recent efforts are devoted to understand the learning capacities of Transformers at the fundamental level

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T17:13:25.912152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 0464476d-d9c3-410a-a98c-df59b7a7c2d6 · inbound

Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent cites this paper.

Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent Transformers versus the EM Algorithm in Multi-class Clustering

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:16:09.615498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.