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Paper Citation Record · LEDGER

The Geometry of Concepts: Sparse Autoencoder Feature Structure

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.19750.

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

pith.paper-citation-record.v1
2410.19750 v2

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 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:12:24.830380Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:39:50.842822Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 eb580ed5-bbb6-4827-919e-cd10a4e64ce4 · inbound

Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders cites this paper.

Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders The Geometry of Concepts: Sparse Autoencoder Feature Structure

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:24.830380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:24.830380Z digest=sha256:d16445818697c3a3df20309e650020ad15717fb78e838b975eb1333e9b809c1b

Observation f8b66d2d-829b-40d4-972f-5710a5b59856 · inbound

Sparsification and Reconstruction from the Perspective of Representation Geometry cites this paper.

Sparsification and Reconstruction from the Perspective of Representation Geometry The Geometry of Concepts: Sparse Autoencoder Feature Structure

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T13:11:38.527027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:11:38.527027Z digest=sha256:a3e3d4ca6ffb19157425fea1f1290a18ce5579d74364a904a43e2ff56110150f

Observation 17c0ee9a-ad58-4570-ab50-e8b399288b88 · inbound

Towards Understanding the Robustness of Sparse Autoencoders cites this paper.

Towards Understanding the Robustness of Sparse Autoencoders The Geometry of Concepts: Sparse Autoencoder Feature Structure

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:46:10.226383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T05:44:24.532548Z digest=sha256:c1e1b01a484d83c9081c679f1bd98bd20a81b5ff1aebc9e8ec898eac6059eca3

Observation 51cf4368-8dec-4ea5-a6a2-f1f726a6503c · inbound

From Token Lists to Graph Motifs: Weisfeiler-Lehman Analysis of Sparse Autoencoder Features cites this paper.

From Token Lists to Graph Motifs: Weisfeiler-Lehman Analysis of Sparse Autoencoder Features The Geometry of Concepts: Sparse Autoencoder Feature Structure

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:16:11.043247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T09:41:01.775116Z digest=sha256:94a9d79536bcb55a8c2ca6d9248df7c6c730e04fe1617a228521c41ac06746e0

Observation bc94049d-f41d-41a1-b8be-8ce4927199d8 · inbound

The Geometric Wall: Manifold Structure Predicts Layerwise Sparse Autoencoder Scaling Laws cites this paper.

The Geometric Wall: Manifold Structure Predicts Layerwise Sparse Autoencoder Scaling Laws The Geometry of Concepts: Sparse Autoencoder Feature Structure

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:56:25.293813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T04:48:19.841691Z digest=sha256:a652152571a7d63cbebea7634a82d559b10a152ff6220f9481c7522041210b40

Observation 67871e06-5b80-48b3-aab9-1db72209b352 · inbound

Where Do Models Find Happiness? Emotion Vectors in Open-Source LLMs cites this paper.

Where Do Models Find Happiness? Emotion Vectors in Open-Source LLMs The Geometry of Concepts: Sparse Autoencoder Feature Structure

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T13:39:50.844439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T05:02:34.714811Z digest=sha256:0444b3160578f46e8e3a7b7b9d2d345267b7b7dfeaa389b4eedf3e82d8527757

Observation d7b8a835-33c6-40bc-9294-e5ec18e9df17 · inbound

Are Single-Token Sparse Autoencoder Features Causally Necessary? Layer-Depth and SAE-Family Effects cites this paper.

Are Single-Token Sparse Autoencoder Features Causally Necessary? Layer-Depth and SAE-Family Effects The Geometry of Concepts: Sparse Autoencoder Feature Structure

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-01T10:03:56.646522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T10:03:56.646522Z digest=sha256:7a8b1d7f03c7410c833cd4f7c147e7faf8abf39214d2b12150693553215064d4