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Paper Citation Record · LEDGER

What Do We Maximize in Self-Supervised Learning?

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2207.10081.

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

pith.paper-citation-record.v1
2207.10081 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:56:59.202089Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T07:23:00.093325Z

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 b9fa943e-ddb7-497a-812a-13bf5d882391 · inbound

Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning cites this paper.

Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning What Do We Maximize in Self-Supervised Learning?

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T15:56:59.202089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:56:59.202089Z digest=sha256:b36de05c3f09bf4a93dfbcfafce2019afb3d85af3c11b7096a91a62f75bab736

Observation 5094a2bc-0d6a-4158-adc0-3b6c84548893 · inbound

LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics cites this paper.

LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics What Do We Maximize in Self-Supervised Learning?

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:23:00.095241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-16T07:22:59.854042Z digest=sha256:6b8523ff72c5f62d3dc1c90903eff63d2fd800e30036d76c98aa44d88445c72f