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Paper Citation Record · LEDGER

Transformers as Support Vector Machines

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2308.16898.

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

pith.paper-citation-record.v1
2308.16898 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:42:09.103451Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:18:13.066258Z

Reference resolution

0 of 0 outbound references displayed

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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 17e09882-94d7-458b-9876-e8d11e230fe2 · inbound

Training Dynamics of In-Context Learning in Linear Attention cites this paper.

Training Dynamics of In-Context Learning in Linear Attention Transformers as Support Vector Machines

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-10T13:42:09.103451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:42:09.103451Z digest=sha256:2a79b120aabf8c9b54c82077ebbb8e51a6b7da8f9e1adb8148e915aad21c5f00

Observation e2fdbd2e-5a2b-49cb-96a9-87b326e24c70 · inbound

Solving Empirical Bayes via Transformers cites this paper.

Solving Empirical Bayes via Transformers Transformers as Support Vector Machines

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T20:21:58.376213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:21:58.376213Z digest=sha256:5200aec1b7fbcf2685ac22f26297592ed666321e412986b907b77b7f677154fd

Observation 2b50d96b-e00c-4ba8-9ca7-4a4b3b64e704 · 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 Transformers as Support Vector Machines

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T06:10:20.263719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:10:20.263719Z digest=sha256:420aff318e56616e101d73be63eb13121e88960b9c1a623a3737453de9e15b0b

Observation 07fe91b1-d007-47f5-8691-5f1cf0e73c51 · inbound

Harnessing Optimization Dynamics for Curvature-Informed Model Merging cites this paper.

Harnessing Optimization Dynamics for Curvature-Informed Model Merging Transformers as Support Vector Machines

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-04T17:03:17.985792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:03:17.985792Z digest=sha256:68c06ceb7aa02b0f1c8768c3c472b9728c4baca6d46cce5f51ccb5fe66025506

Observation 93817fb6-e601-4ce0-93cc-2b2fdcd1cfb7 · inbound

Bilevel Data Curation for LLM Fine-tuning: Offline Selection and Online Self-Refining Generation cites this paper.

Bilevel Data Curation for LLM Fine-tuning: Offline Selection and Online Self-Refining Generation Transformers as Support Vector Machines

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-03T20:12:52.437823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:12:52.437823Z digest=sha256:da0bc622d34d32fcbf08adcad8a191390ec1a1f55a87bd1d0593ac5805f90b80

Observation 4284b47c-05ef-4417-8c97-49b6a6591963 · inbound

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge cites this paper.

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge Transformers as Support Vector Machines

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-03T05:27:44.313983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:27:44.313983Z digest=sha256:ea735315958f137bdabb1ee2713b12a4536986b1d0fd817307765bf57e0a16e8

Observation 05e6f10a-8aec-477a-9e57-9ffc25a7b167 · inbound

The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems cites this paper.

The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems Transformers as Support Vector Machines

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-02T22:58:10.372848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T22:58:10.372848Z digest=sha256:a22fba34601200decad2b1a68ec96d14cccad64c1783b73f6af21591c02febb5

Observation 1f989db2-7ee9-42ce-a9c8-08e7071c195a · inbound

Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs cites this paper.

Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs Transformers as Support Vector Machines

Reference 55

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T08:56:02.695029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T16:23:50.751356Z digest=sha256:94007c89b00a6d1269e5b2a2953fadc0a8650b5a5509fc2a413907ebb5939111

Observation 023a0426-4a55-44c8-a0d0-33d006fe45e0 · inbound

The Implicit Bias of Depth: From Neural Collapse to Softmax Codes cites this paper.

The Implicit Bias of Depth: From Neural Collapse to Softmax Codes Transformers as Support Vector Machines

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:26:38.909933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-25T05:26:15.556205Z digest=sha256:a5559deb91677a9c312bfe8e4f8a41d8a551117d164a3ffc88b9bf789145c10c

Observation 646c3f99-da1e-4d72-9e11-0c8a26d83dc1 · inbound

Tight Sample Complexity of Transformers cites this paper.

Tight Sample Complexity of Transformers Transformers as Support Vector Machines

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:57:29.147616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T17:33:48.373948Z digest=sha256:51aee4c9c58b5494a8be6114ebec27cb52928f9744d27c6bb725f64d3f79f1a8

Observation 5d8fb22b-1525-4501-bf10-fa9568080a4e · inbound

Phase Transitions in Attention: A Bayesian Theory of Copy Head Emergence cites this paper.

Phase Transitions in Attention: A Bayesian Theory of Copy Head Emergence Transformers as Support Vector Machines

Reference 62

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:18:13.068660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T08:13:40.546738Z digest=sha256:fa7cc54fe8687218d76698282823b3e84c835d16d09382c824bd04795e540e90

Observation 0a6e143c-3a8b-4c0a-a4b2-e8967f3a26b6 · inbound

Frontier Language Models Struggle to Copy: Text Can Be Better Viewed in 2D cites this paper.

Frontier Language Models Struggle to Copy: Text Can Be Better Viewed in 2D Transformers as Support Vector Machines

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-01T21:30:58.130989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:30:58.130989Z digest=sha256:acf3eac702b7b592a6ebdebf86f8c56b3683bbbb6c3c8a438cbc89aea96cee1c

Observation ca89681d-e3e9-4c19-97de-d86074f75c14 · inbound

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex cites this paper.

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex Transformers as Support Vector Machines

Reference 202

Resolution
unresolved
no resolver link, observed 2026-07-31T23:52:06.947791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:52:06.947791Z digest=sha256:f046a11492b76b5363209ee3127c6fee80a6bbe5d2dac36dfc96031d1c15e632