Paper Citation Record · LEDGER

High Fidelity Visualization of What Your Self-Supervised Representation Knows About

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2112.09164.

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

pith.paper-citation-record.v1
2112.09164 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 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:19:58.937022Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T18:13:49.202210Z

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 1123a7f6-a6ff-4b32-aaf2-20df1e328d80 · inbound

Hierarchical Text-Conditional Image Generation with CLIP Latents cites this paper.

Hierarchical Text-Conditional Image Generation with CLIP Latents High Fidelity Visualization of What Your Self-Supervised Representation Knows About

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-10T16:55:57.743745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cbe81aeb-bed7-46ad-843d-618ff3ad9092 · inbound

EchoWorld: Learning Motion-Aware World Models for Echocardiography Probe Guidance cites this paper.

EchoWorld: Learning Motion-Aware World Models for Echocardiography Probe Guidance High Fidelity Visualization of What Your Self-Supervised Representation Knows About

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T12:19:58.937022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d825b6a-8743-4da8-8854-eebe08495093 · inbound

CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning cites this paper.

CheXWorld: Exploring Image World Modeling for Radiograph Representation Learning High Fidelity Visualization of What Your Self-Supervised Representation Knows About

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T12:04:31.758271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07071235-9b22-4a46-b527-ecd90daf1f6d · inbound

Image Classification Using a Diffusion Model as a Pre-Training Model cites this paper.

Image Classification Using a Diffusion Model as a Pre-Training Model High Fidelity Visualization of What Your Self-Supervised Representation Knows About

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T22:35:15.444686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73e36fe5-fbac-4be2-bb7f-ae445d50d960 · inbound

Towards Controllable Image Generation through Representation-Conditioned Diffusion Models cites this paper.

Towards Controllable Image Generation through Representation-Conditioned Diffusion Models High Fidelity Visualization of What Your Self-Supervised Representation Knows About

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:13:49.203774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fe32be1a-2fea-43fe-ba4f-00bd4fa36e1c · inbound

Representation-Conditioned Diffusion Models for Guided Training Data Generation cites this paper.

Representation-Conditioned Diffusion Models for Guided Training Data Generation High Fidelity Visualization of What Your Self-Supervised Representation Knows About

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:13:48.437151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.