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Paper Citation Record · LEDGER

Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2501.06366.

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

pith.paper-citation-record.v1
2501.06366 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:46:49.327720Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T22:20:10.057416Z

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 527e1cdc-f964-402f-998d-e9a759688c1b · inbound

A Distributional Perspective on Pearl's Causal Hierarchy: From Marginal to Joint and Individualized Potential Outcomes cites this paper.

A Distributional Perspective on Pearl's Causal Hierarchy: From Marginal to Joint and Individualized Potential Outcomes Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T15:46:49.327720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:46:49.327720Z digest=sha256:e6d918e2827c807282f28d0b7a1474cd9cbb2b9782bd16cc5120864157f27f56

Observation 42a22d94-0b26-4d26-a80b-7faaa6af9024 · inbound

Residues of a tropical zeta function for convex domains cites this paper.

Residues of a tropical zeta function for convex domains Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-07-04T22:20:10.059569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-04T22:12:12.818774Z digest=sha256:f18c74fc48fcb16ed3b1dc065f65df42d384e35c387e2e558616224adfe6dea0

Observation 70c0701e-0681-4093-aeea-7d42ad67a1d3 · inbound

Fairness under uncertainty in sequential decisions cites this paper.

Fairness under uncertainty in sequential decisions Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-09T22:44:15.056811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-09T22:23:30.041047Z digest=sha256:8f135a908f08c5d2d81bb97954a33e5330e19434a92e45f19cb47cca03a4fe5b

Observation 434910a5-4f2a-43a2-87be-ca8fffb3d08e · inbound

Counterfactually Safe Reinforcement Learning cites this paper.

Counterfactually Safe Reinforcement Learning Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T00:04:06.869339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-29T23:48:41.383288Z digest=sha256:b6acffc6ad9d3e7edec6208cb184a1f5220dfeac9a245be70b4fa1c063f6812c

Observation 91242242-3dff-4891-ba6a-1769ed96de52 · inbound

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning cites this paper.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-14T04:32:28.212392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:32:28.212392Z digest=sha256:f1317111ebb05108cce5df5eba3ff06f8b48cddae93d1179d91d6faff251afbb