Paper Citation Record · LEDGER

Interpreting the Repeated Token Phenomenon in Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2503.08908.

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

pith.paper-citation-record.v1
2503.08908 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:31:18.044410Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d78de024-8941-40d9-92e2-15d09c2c8a94 · inbound

Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free cites this paper.

Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free Interpreting the Repeated Token Phenomenon in Large Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:04:34.949399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0e012156-7341-48ac-9b01-fb96607b4c76 · inbound

Transformers Don't Need LayerNorm at Inference Time: Scaling LayerNorm Removal to GPT-2 XL and the Implications for Mechanistic Interpretability cites this paper.

Transformers Don't Need LayerNorm at Inference Time: Scaling LayerNorm Removal to GPT-2 XL and the Implications for Mechanistic Interpretability Interpreting the Repeated Token Phenomenon in Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T20:31:18.044410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2700f50-151a-45ab-befb-589ee67e949b · inbound

Taming Outlier Tokens in Diffusion Transformers cites this paper.

Taming Outlier Tokens in Diffusion Transformers Interpreting the Repeated Token Phenomenon in Large Language Models

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:41:07.355579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dd81ed50-db08-4f37-bd51-2a86779a10e6 · inbound

The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity cites this paper.

The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity Interpreting the Repeated Token Phenomenon in Large Language Models

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:21:08.552079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fe520b52-5034-4ffe-b4d6-9afde660ccb8 · inbound

Registers Matter for Pixel-Space Diffusion Transformers cites this paper.

Registers Matter for Pixel-Space Diffusion Transformers Interpreting the Repeated Token Phenomenon in Large Language Models

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:08:54.081650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d4833ae4-1148-4208-a113-f82db442c40d · inbound

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers Interpreting the Repeated Token Phenomenon in Large Language Models

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:32:46.712918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7af41a46-775e-400a-8893-099be0bba0aa · inbound

Extracting Algorithms in Pre-trained LLMs: A Case on Hidden Markov Models cites this paper.

Extracting Algorithms in Pre-trained LLMs: A Case on Hidden Markov Models Interpreting the Repeated Token Phenomenon in Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T10:12:29.133133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.