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Paper Citation Record · LEDGER

Emergence and Function of Abstract Representations in Self-Supervised Transformers

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.05361.

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

pith.paper-citation-record.v1
2312.05361 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 2026-08-07T04:57:41.454366Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:40:36.362755Z

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 7fdf537a-890d-4647-a2db-1dfd4e890fb7 · inbound

Large Language Models and Emergence: A Complex Systems Perspective cites this paper.

Large Language Models and Emergence: A Complex Systems Perspective Emergence and Function of Abstract Representations in Self-Supervised Transformers

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T04:57:41.454366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:57:41.454366Z digest=sha256:da7b4a54fb304dae06dfec8d0b465390b670499f8c1ee24ff466a3d85839dfce

Observation 4fe942c1-1f9a-462d-bab2-254b150d9f07 · inbound

Deep sequence models tend to memorize geometrically; it is unclear why cites this paper.

Deep sequence models tend to memorize geometrically; it is unclear why Emergence and Function of Abstract Representations in Self-Supervised Transformers

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:40:36.364617Z

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=pdf_text observed=2026-05-21T20:38:18.005002Z digest=sha256:d947a573b775214ff0c140b9cfb7aaf2be785e62fbbfc8babc2cacb18232e993