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Paper Citation Record · LEDGER

Transcendence: Generative Models Can Outperform The Experts That Train Them

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.11741.

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

pith.paper-citation-record.v1
2406.11741 v4

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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:24:54.934427Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T14:54:29.369507Z

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 d3085331-c4bf-476c-833d-0630c66e23c3 · inbound

Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss cites this paper.

Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss Transcendence: Generative Models Can Outperform The Experts That Train Them

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-09T21:24:54.934427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T21:24:54.934427Z digest=sha256:10482411a03e5bfabf9b953da93e2717e6bfbe5faedfc84b533e6e029d57f90c

Observation 0162c47a-29ff-4551-81c6-863c813c83a4 · inbound

Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges cites this paper.

Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges Transcendence: Generative Models Can Outperform The Experts That Train Them

Reference 67

Resolution
metadata mismatch
local_arxiv, observed 2026-08-09T14:54:29.375055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-09T14:54:29.300229Z digest=sha256:1d6c1d33de0240766daae514d7e9cb1385782d3b2a5fc2da391654e2232dcb45