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Paper Citation Record · LEDGER

Reward Centering

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.09999.

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

pith.paper-citation-record.v1
2405.09999 v2

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 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:20:14.470216Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T00:03:51.939547Z

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 6a234d97-1b19-4d65-bd3a-bd2b23d3b1a8 · inbound

Harnessing the Power of Reinforcement Learning for Adaptive MCMC cites this paper.

Harnessing the Power of Reinforcement Learning for Adaptive MCMC Reward Centering

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T21:20:14.470216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:20:14.470216Z digest=sha256:69829d5e69f9773ea8e65162092e308204b29746c65d816d9fe285f12079460f

Observation 4535117f-df57-4af2-9837-47ca0f6d0c85 · inbound

Learning from Expert Factors: Trajectory-level Reward Shaping for Formulaic Alpha Mining cites this paper.

Learning from Expert Factors: Trajectory-level Reward Shaping for Formulaic Alpha Mining Reward Centering

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T13:48:52.362113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:48:52.362113Z digest=sha256:7d52e61dead4fbb4683d6793edb786a986cea591cdee256d8f9379214bd7603d

Observation 47b0d747-7891-485f-8593-5fc5accb7573 · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control Reward Centering

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:15:49.953334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T20:04:56.512544Z digest=sha256:c4e519974fe26a4a009872ed5beab402373a1e7065d3dea361ad6b5f603e134f

Observation fb70e78c-d09b-43d9-8fc2-73fbd9397a60 · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control Reward Centering

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-19T17:12:41.393233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T17:08:31.770889Z digest=sha256:ecba72dd50a823c24033c76aba432c2d31f4d93b966b8416d85c1f7678d00268

Observation 85911fbf-9f48-4fde-95b2-9712883279ef · inbound

Graph Transformers and Stabilized Reinforcement Learning for Large-Scale Dynamic Routing Modulation and Spectrum Allocation in Elastic Optical Networks cites this paper.

Graph Transformers and Stabilized Reinforcement Learning for Large-Scale Dynamic Routing Modulation and Spectrum Allocation in Elastic Optical Networks Reward Centering

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:10:43.189533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T18:47:04.091987Z digest=sha256:b69d20574733c17f3aa8f93bea313b61473f82459284e146a48fcfb096e4e4db

Observation adc8559f-f14b-4e9e-bd51-5aeb34727d4f · inbound

Graph Transformers and Stabilized Reinforcement Learning for Large-Scale Dynamic Routing Modulation and Spectrum Allocation in Elastic Optical Networks cites this paper.

Graph Transformers and Stabilized Reinforcement Learning for Large-Scale Dynamic Routing Modulation and Spectrum Allocation in Elastic Optical Networks Reward Centering

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-21T00:03:51.942284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T00:02:01.826213Z digest=sha256:587e82d3df93e86a3b920ff669a24b6578e6257725e7760f5dbbe65aa46ab648