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Paper Citation Record · LEDGER

Foundation Models for Semantic Novelty in Reinforcement Learning

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.04878.

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

pith.paper-citation-record.v1
2211.04878 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 2026-08-03T06:30:56.289259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T11:13:21.565082Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 7c012584-c432-4aa9-9010-645d751f6c1f · inbound

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution Foundation Models for Semantic Novelty in Reinforcement Learning

Reference 126

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:12:31.530930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=arxiv_source observed=2026-05-16T08:12:30.984870Z digest=sha256:a1c2c678efc9a926768d39d4112ffdd786cb63bb344b10ec0cd660b603b7cbe7

Observation 099b8cf7-d684-4de6-97dd-e85f8e3ac597 · inbound

Right Makes Might: Aligning Verified Hidden States Empowers RL Reasoning cites this paper.

Right Makes Might: Aligning Verified Hidden States Empowers RL Reasoning Foundation Models for Semantic Novelty in Reinforcement Learning

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T02:06:27.283338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-06-28T11:13:21.565082Z digest=sha256:85ff751005e73edd7db3381e15e9900c20de78f9d402bd491c2f9edf15d87c3c