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Paper Citation Record · LEDGER

Representation Topology Divergence: A Method for Comparing Neural Network Representations

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2201.00058.

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

pith.paper-citation-record.v1
2201.00058 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:17:55.758852Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T15:47:06.965245Z

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 eed6575a-9b18-47f0-ae6c-cf969e7ac68e · inbound

TOAST: Transformer Optimization using Adaptive and Simple Transformations cites this paper.

TOAST: Transformer Optimization using Adaptive and Simple Transformations Representation Topology Divergence: A Method for Comparing Neural Network Representations

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-23T19:48:23.061037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-23T19:46:07.124996Z digest=sha256:69b81a1abfac9090633d09dcc570977d9c097973122883049ecc41dd83c74bad

Observation 05dc27ee-b118-424f-a936-014a0281c8c8 · inbound

DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models cites this paper.

DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models Representation Topology Divergence: A Method for Comparing Neural Network Representations

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T11:47:24.789560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T11:47:24.789560Z digest=sha256:7a535ca9d7579104fce819327e13eefa01da7d655a7c8f003b78a4f970d28928

Observation ee59f2d0-8ab1-4510-abcc-ebae2f046d0c · inbound

Topology-Aware Representation Alignment for Semi-Supervised Vision-Language Learning cites this paper.

Topology-Aware Representation Alignment for Semi-Supervised Vision-Language Learning Representation Topology Divergence: A Method for Comparing Neural Network Representations

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:41:25.674437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-07T14:03:24.505277Z digest=sha256:725b6307e7266ca362a3fd441a16585e7cad7f90ec8f48c029025a2c20c8ed47

Observation 7b5ca715-e748-4b6b-829d-d17be964b815 · inbound

From Layers to Networks: Comparing Neural Representations via Diffusion Geometry cites this paper.

From Layers to Networks: Comparing Neural Representations via Diffusion Geometry Representation Topology Divergence: A Method for Comparing Neural Network Representations

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-20T20:03:43.639570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T20:02:14.293587Z digest=sha256:be9523a3dd0115b84f6829af0313696d213c283a5e724824dce7f8953308882a

Observation 0ea46acd-00e5-4961-adde-11c12bbd98f7 · inbound

Symmetric Divergence and Normalized Similarity: A Unified Topological Framework for Representation Analysis cites this paper.

Symmetric Divergence and Normalized Similarity: A Unified Topological Framework for Representation Analysis Representation Topology Divergence: A Method for Comparing Neural Network Representations

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-02T15:47:06.967229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-27T23:18:34.206475Z digest=sha256:463d70e6161939a63d4ee0715bdcaab537486b77b5422958252f825d1a3993e4

Observation 99bad67a-8f11-4798-a8d3-1e4ee9868bcc · inbound

Multimodal Model Diffing for Feature Discovery and Control cites this paper.

Multimodal Model Diffing for Feature Discovery and Control Representation Topology Divergence: A Method for Comparing Neural Network Representations

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:55.758852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:55.758852Z digest=sha256:9cf57dc785e9a6d852d48717d493b37eb8d9ee6e09302c881c60ad825a66051a