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Paper Citation Record · LEDGER

Singular Vectors of Attention Heads Align with Features

As of 7 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 1 inbound Pith citation observation for arXiv:2602.13524.

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

pith.paper-citation-record.v1
2602.13524 v2

Coverage vector

measured 6 of 6 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:38:14.742535Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T04:43:05.157923Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

6 of 6 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e0e46d1f-7a1e-440a-a1d7-322fc1782503 · outbound

This paper cites Language Models Use Trigonometry to Do Addition.

Singular Vectors of Attention Heads Align with Features Language Models Use Trigonometry to Do Addition

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T23:38:14.505229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:38:14.505229Z digest=sha256:f7373bc4ce17d580f563a27e523134a4a32e6de01529d43cdd919fd8edc6b5b0

Observation 7ff6c105-818a-43d7-976a-e3106d3dae88 · outbound

This paper cites In particular, if there exists a feasible(x′ 2, y′.

Singular Vectors of Attention Heads Align with Features In particular, if there exists a feasible(x′ 2, y′

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-02T23:38:14.635972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:38:14.635972Z digest=sha256:331259ea85dce13cc2f5619a25bb4d85beaf3d3d7a5e489f68dd516bc47b94c4

Observation 7bdaf871-d3b9-4b34-ab2a-3d2b67a66a1b · outbound

This paper cites an unresolved cited work.

Singular Vectors of Attention Heads Align with Features Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-02T23:38:14.683149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:38:14.683149Z digest=sha256:dfb9974e2f47aea6aae2563bab839b06a97267395e4b4ec1014424437407a5ff

Observation 2770f227-ab0d-4879-a148-7e3c8bb8868d · outbound

This paper cites an unresolved cited work.

Singular Vectors of Attention Heads Align with Features Unresolved cited work

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-02T23:38:14.742535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:38:14.742535Z digest=sha256:b2d8dabbe85b054eef106b390743f8096b2be905a203a4bb64454d7cff3c78e2

Observation d610a1c0-cf66-4de5-b807-533ef22ec407 · outbound

This paper cites Open Problems in Mechanistic Interpretability.

Singular Vectors of Attention Heads Align with Features Open Problems in Mechanistic Interpretability

Reference 1972

Resolution
unresolved
no resolver link, observed 2026-08-02T23:38:14.568953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:38:14.568953Z digest=sha256:8b9642a36d79d10d8e52276232799c9bb300f08f045def8d6a9e5f55ce5e8c90

Observation 0a4818ae-0e65-400d-a70a-8cfe718e497e · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Singular Vectors of Attention Heads Align with Features Scaling and evaluating sparse autoencoders

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T23:38:14.421245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:38:14.421245Z digest=sha256:3481d608f56fdc715785380c61a9e6e694a736dd4e024ee188207c6ea7901b29

Pith citing papers

Observation bb742b08-180c-414d-a25b-451216455fc5 · inbound

Complexity-Guided Component-wise Initialization for Language Model Pretraining cites this paper.

Complexity-Guided Component-wise Initialization for Language Model Pretraining Singular Vectors of Attention Heads Align with Features

Reference 3

Resolution
malformed identifier
no resolver link, observed 2026-07-13T04:43:05.157923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T04:43:05.157923Z digest=sha256:4a81eb1ef12647e9300a22de93f6aa635d65fe5a1aac265391413904265ce911