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Paper Citation Record · LEDGER

Learning to Reason in Large Theories without Imitation

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1905.10501.

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

pith.paper-citation-record.v1
1905.10501 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:35:27.215193Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T22:19:00.432407Z

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 dc2d2180-32fc-467f-b258-5a1f58e7da45 · inbound

Generative Language Modeling for Automated Theorem Proving cites this paper.

Generative Language Modeling for Automated Theorem Proving Learning to Reason in Large Theories without Imitation

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-23T05:18:10.701748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-23T05:18:10.620262Z digest=sha256:cea6e652f1fe0577307c73e39f8500fb434bdfd46e60906bcde5b004c367085b

Observation 88f5481c-c902-4f49-895e-0ca96c32d96c · inbound

MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics cites this paper.

MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics Learning to Reason in Large Theories without Imitation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-16T20:03:04.453486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-16T20:03:04.424625Z digest=sha256:c74a772df4118d3f8fdd4260ddde416f0cfc29564a2864e6fe4fef272e0bb3c2

Observation 38355c8e-54d8-4cef-bccc-f06f0e035f20 · inbound

Rango: Adaptive Retrieval-Augmented Proving for Automated Software Verification cites this paper.

Rango: Adaptive Retrieval-Augmented Proving for Automated Software Verification Learning to Reason in Large Theories without Imitation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T12:35:27.215193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:35:27.215193Z digest=sha256:50761a161a5b31ca1a5d38e3340d920d15729d35726b70575a2733422ca211ba

Observation 2e3c5bf6-5b0d-46e1-ba9a-f133544e4b90 · inbound

Solving Formal Math Problems by Decomposition and Iterative Reflection cites this paper.

Solving Formal Math Problems by Decomposition and Iterative Reflection Learning to Reason in Large Theories without Imitation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T15:42:05.567274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:42:05.567274Z digest=sha256:3139635a029c1c266729b69ed1ee862d3195146546883c877e6319cca5b19217

Observation f59bb14a-b67d-4b17-8ded-9c1d4e7aa32f · inbound

Planning to Hammer: Difficulty-Aware Decomposition for Automating Rocq Proofs cites this paper.

Planning to Hammer: Difficulty-Aware Decomposition for Automating Rocq Proofs Learning to Reason in Large Theories without Imitation

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T22:19:00.433815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T23:39:24.268789Z digest=sha256:85c0eadcaf1dff9364d1fa7f6b8d237978ece898294e0812fec721434d4cc942

Observation d9711988-8a67-4a45-887d-99da0c0bc5f7 · inbound

Planning to Hammer: Difficulty-Aware Decomposition for Automating Rocq Proofs cites this paper.

Planning to Hammer: Difficulty-Aware Decomposition for Automating Rocq Proofs Learning to Reason in Large Theories without Imitation

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-02T11:07:56.561219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:07:56.561219Z digest=sha256:d01165c2887c83ce43f2cf1b5fe67866095dd4f46653c9af26610df189a339e9