Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
I-Con: A Unifying Framework for Representation Learning
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.16929.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T14:52:24.285184Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T00:25:09.961101Z
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 913822dd-9408-4016-852b-5bb9354c221b · inbound
Harmonic Loss Trains Interpretable AI Models cites this paper.
Harmonic Loss Trains Interpretable AI Models I-Con: A Unifying Framework for Representation Learning
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T14:52:24.285184Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e5923fa0-b284-48f3-87ac-793ff51580bc · inbound
Learning Minimal Representations of Fermionic Ground States cites this paper.
Learning Minimal Representations of Fermionic Ground States I-Con: A Unifying Framework for Representation Learning
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T16:50:10.671559Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2e95ea3e-80c6-447f-8f76-1502a52c2cce · inbound
Understanding Self-Supervised Learning via Latent Distribution Matching cites this paper.
Understanding Self-Supervised Learning via Latent Distribution Matching I-Con: A Unifying Framework for Representation Learning
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:51:32.004576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 765a5b99-db53-4a01-bf15-f5cf104ab18e · inbound
Understanding Self-Supervised Learning via Latent Distribution Matching cites this paper.
Understanding Self-Supervised Learning via Latent Distribution Matching I-Con: A Unifying Framework for Representation Learning
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T00:13:53.193785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b03a3de1-b669-491c-85f4-3f78b7aed1eb · inbound
Understanding Self-Supervised Learning via Latent Distribution Matching cites this paper.
Understanding Self-Supervised Learning via Latent Distribution Matching I-Con: A Unifying Framework for Representation Learning
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T00:25:09.962468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation aef7ce90-2fdc-44d4-8a1f-eed5cfe464fe · inbound
Understanding Self-Supervised Learning via Latent Distribution Matching cites this paper.
Understanding Self-Supervised Learning via Latent Distribution Matching I-Con: A Unifying Framework for Representation Learning
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T15:01:34.976937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.