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Paper Citation Record · LEDGER

Rethinking Reflection in Pre-Training

As of 19 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.04022.

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

pith.paper-citation-record.v1
2504.04022 v1

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 2026-07-19T06:30:13.599613+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-05T10:18:18.717871Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-05T10:20:57.237283Z

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 6e0d4383-d98e-4329-bae7-b28ca559b054 · inbound

Reinforcement Learning for Reasoning in Large Language Models with One Training Example cites this paper.

Reinforcement Learning for Reasoning in Large Language Models with One Training Example Rethinking Reflection in Pre-Training

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:51:05.097590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

source=pdf_text observed=2026-05-15T19:51:04.779597Z digest=sha256:e6ddc16ac846faf264e1cf469c398cfbf0bbf04b8689492dc34875d6e764a8e8

Observation c5f341ca-6c69-4efc-91c7-bdbe9aabc616 · inbound

Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration cites this paper.

Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration Rethinking Reflection in Pre-Training

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:36:53.752419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

source=pdf_text observed=2026-05-18T22:33:01.074518Z digest=sha256:526c5537c13629f3b075638e9b693509d313bbdcddc542751f709bffc01daddd

Observation ecb10b1d-f835-47cd-87eb-b986a7e0759a · inbound

Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards cites this paper.

Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards Rethinking Reflection in Pre-Training

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-18T14:26:28.217277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

source=pdf_text observed=2026-05-18T14:24:48.666197Z digest=sha256:870b5f305280701239093cf48321cbab16d646575e985825340de5a1244238c7

Observation 7a64fd7d-c393-4110-94f6-f1818ad00ff2 · inbound

How Much Thinking is Enough? Quantifying and Understanding Redundancy in LLM Reasoning cites this paper.

How Much Thinking is Enough? Quantifying and Understanding Redundancy in LLM Reasoning Rethinking Reflection in Pre-Training

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-05T10:20:57.239715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

source=pdf_text observed=2026-07-05T10:18:18.717871Z digest=sha256:9f06383f8035bd377dcdbc014034ed19ee1296f742b740b53f6676b87ad0a087

Observation 283fed06-b34b-4ef7-9aa5-28b5431b5e8f · inbound

On Advantage Estimates for Max@K Policy Gradients cites this paper.

On Advantage Estimates for Max@K Policy Gradients Rethinking Reflection in Pre-Training

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:06:56.418746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

source=pdf_text observed=2026-06-28T02:21:57.143016Z digest=sha256:1c895a99f15f4d90195902a095253f2e95553c909f8b17e7d132b15f597b8b1c

Observation cecee2b2-8406-4f3c-8593-80399a10b817 · inbound

OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation cites this paper.

OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation Rethinking Reflection in Pre-Training

Reference 84

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:16:56.961703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

source=pdf_text observed=2026-06-28T02:17:30.974692Z digest=sha256:986a9fcda26214fd99b2f29ee5212fb73c67efd991f870aea3dcdd4df75a28a2