Paper Citation Record · LEDGER

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training

As of 7 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2608.05148.

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

pith.paper-citation-record.v1
2608.05148 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:19:48.909099Z

measured 12 of 12 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

verified exact0
verified fuzzy2
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6159d5fd-f597-4de4-8f06-d6989927b676 · outbound

This paper cites ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.346566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e803771a-d9e7-423a-8ddb-e59a979f2f64 · outbound

This paper cites SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.415270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13c2b07c-2ebb-4557-a12f-165b02759f17 · outbound

This paper cites Olmo 3.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training Olmo 3

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.483282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cd11cc4-7451-4ff0-aa52-fd3874a88705 · outbound

This paper cites Mirac Suzgun, Nathan Scales, Nathanael Schärli, Se- bastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc Le, Ed Chi, Denny Zhou, and Jason Wei.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training Mirac Suzgun, Nathan Scales, Nathanael Schärli, Se- bastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc Le, Ed Chi, Denny Zhou, and Jason Wei

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.542240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b4c3e4-c2f2-4399-95db-0521d2253862 · outbound

This paper cites InFindings of the Association for Computational Lin- guistics: ACL 2023, pages 13003–13051, Toronto, Canada.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training InFindings of the Association for Computational Lin- guistics: ACL 2023, pages 13003–13051, Toronto, Canada

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:19:49.503757Z

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.

Observation e82cc399-80f5-4482-aec9-d8c1d6c0af8b · outbound

This paper cites InFindings of the Association for Computa- tional Linguistics: ACL 2025, pages 6980–7008.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training InFindings of the Association for Computa- tional Linguistics: ACL 2025, pages 6980–7008

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:19:49.349750Z

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.

Observation e3130e9f-7fed-4c69-809e-70e55ac6b105 · outbound

This paper cites (filtered).

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training (filtered)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.909099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d81c660d-93d4-4273-92f3-c62ff223fc21 · outbound

This paper cites Leveraging Procedural Generation to Benchmark Reinforcement Learning.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training Leveraging Procedural Generation to Benchmark Reinforcement Learning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.168776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8243ab9c-545c-4a64-ae57-1f679398626e · outbound

This paper cites Physics of Language Models: Part 1, Learning Hierarchical Language Structures.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training Physics of Language Models: Part 1, Learning Hierarchical Language Structures

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.084542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1efcf01d-8ee9-4a49-a9ea-40b9d25b8845 · outbound

This paper cites DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.744100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f3fee1-8c50-477e-bbe3-f68723bf3f83 · outbound

This paper cites Zeyuan Allen-Zhu and Yuanzhi Li.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training Zeyuan Allen-Zhu and Yuanzhi Li

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.027607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dba44b9-c062-45d9-83a3-ba6b37c89977 · outbound

This paper cites Procedural Pretraining: Warming Up Language Models with Abstract Data.

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training Procedural Pretraining: Warming Up Language Models with Abstract Data

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-06T04:19:48.253995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.