Paper Citation Record · LEDGER

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning

As of 23 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2608.08743.

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

pith.paper-citation-record.v1
2608.08743 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:32:28.279296Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

40 of 40 outbound references displayed

verified exact2
verified fuzzy15
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6fc0fdac-d787-4a10-9182-b8e3d5cb80bb · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:28.000230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5ac820d-c3d2-4669-9be8-6dae87c70217 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.412296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 08738ae3-efc4-45a7-bf4d-f94502a3a6f5 · outbound

This paper cites and Jiang, N.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning and Jiang, N

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:29.392799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b58e3e87-c966-48bb-9251-59b5d2181b4a · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.371497Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 14b53a59-bde5-4f45-9e2d-ef48271b5a2f · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.343746Z

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Observation db60f650-21fb-46d4-ba92-98c03b3baabc · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.318399Z

Source-reported events for the cited work

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Observation ff6fa425-5199-402c-a001-035b2d87df7c · outbound

This paper cites and Hansen, C.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning and Hansen, C

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:29.299083Z

Source-reported events for the cited work

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Observation 8d34be8b-318d-4035-b788-e408aa993c5d · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.279439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0cf47483-24a2-4958-8436-cffa16a59672 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.263006Z

Source-reported events for the cited work

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Observation 85580858-90f7-443e-8f76-d73bde7c6cb9 · outbound

This paper cites Counterfactual fairness: removing direct effects through regularization.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Counterfactual fairness: removing direct effects through regularization

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 025f486c-9489-4f35-8e56-6aea85894ebf · outbound

This paper cites Contextual Markov Decision Processes.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Contextual Markov Decision Processes

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:28.076578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf2a5fc2-4861-46f2-91f1-f95286416b47 · outbound

This paper cites A., Ashburn-Nardo, L., Stewart, J.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning A., Ashburn-Nardo, L., Stewart, J

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:29.242765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 27777044-4ec5-4abb-9f4a-a508d243a5d4 · outbound

This paper cites Fast Rates for the Regret of Offline Reinforcement Learning.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Fast Rates for the Regret of Offline Reinforcement Learning

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da517c1b-98b8-4487-b4fc-0af966bfac85 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.223007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5991f9a7-9177-4456-b5e7-8b88475acb78 · outbound

This paper cites and Langford, J.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning and Langford, J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:29.201784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cb51405a-a3e4-4e3b-a4f7-facb0db92a0c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Adam: A Method for Stochastic Optimization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:28.109209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b8896e4-e391-45f2-a0cd-f39b76e294f1 · outbound

This paper cites (2005).Quantile Regression.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning (2005).Quantile Regression

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:29.182460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 44e546f5-1dad-4d1e-9b60-22d34f21186e · outbound

This paper cites and Bassett, G.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning and Bassett, G

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:29.159455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 55f5954c-b607-411b-8cd4-be7fde8a1f08 · outbound

This paper cites Counterfactual Fairness.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Counterfactual Fairness

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T04:32:28.129831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80d0804d-1992-4a3f-9675-b282d9ef816e · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.139367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a0bd24be-6216-44cf-8354-3846ae1ffa8f · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.116743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a734d2a6-c6c2-49ff-b860-77de7b28061e · outbound

This paper cites T., Dean, S., Rolf, E., Simchowitz, M., and Hardt, M.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning T., Dean, S., Rolf, E., Simchowitz, M., and Hardt, M

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:29.096711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 241fbc64-e571-4111-846b-5beae18f0679 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.077649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d4470e6e-38fe-4339-80bf-e2ba620924d3 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.051470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d6b5c338-2619-409f-ba22-b6520c3c0be6 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:29.029108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e30e7557-4e6c-4433-bacd-72e525a6c535 · outbound

This paper cites C., Krishnamurthy, A., Bartlett, P., and Kakade, S.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning C., Krishnamurthy, A., Bartlett, P., and Kakade, S

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.997577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 77449e86-9bcb-43ec-916b-f2bce1f446d5 · outbound

This paper cites D., Thomas, L., Newman, S., Marinec, N., Krauss, J., Chen, J., Wu, Z., and Bohnert, A.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning D., Thomas, L., Newman, S., Marinec, N., Krauss, J., Chen, J., Wu, Z., and Bohnert, A

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.977783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4a5ec70c-d8db-46a9-8dc2-c592c806a9ab · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:28.957278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 05f18095-e5a1-4d5c-ad20-16d7679b58c3 · outbound

This paper cites and Perktold, J.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning and Perktold, J

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.937412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8d962cf5-1dc0-45e9-9729-e3055dd44cd7 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:28.918254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

This paper cites Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing.

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

Reference 31

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Source-reported events for the cited work

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Observation b403ab00-52ce-4be6-b882-83a222626564 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:28.899392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 43a3d218-9cee-458c-a25d-c195561d50c7 · outbound

This paper cites offered admission.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning offered admission

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.877450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ad520388-ddf5-47bd-a4fb-df1b6724fdc0 · outbound

This paper cites F={w T ϕ(s, a) :w∈R d,∥w∥ 1 ≤ B}, where ϕ is a feature map ˜S × A →Rd with ∥ϕ(s, a)∥∞ ≤1 and component functions {ϕi(s, a)}d i=1.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning F={w T ϕ(s, a) :w∈R d,∥w∥ 1 ≤ B}, where ϕ is a feature map ˜S × A →Rd with ∥ϕ(s, a)∥∞ ≤1 and component functions {ϕi(s, a)}d i=1

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.852587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6bfe92bf-1427-462d-993b-b907e76f82ae · outbound

This paper cites LetTbe the Bellman optimality operator.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning LetTbe the Bellman optimality operator

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.827924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a55c7ff4-ceba-468c-8f2a-cdab28b2e414 · outbound

This paper cites Full”, “Unaware.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Full”, “Unaware

Reference 36

Resolution: verified exact; raw_fallback, observed 2026-08-14T04:32:28.449631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fd4f8929-fce9-4653-843a-b6e37ac90f00 · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:28.802683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d8435553-83ae-4a32-aaf8-5d87715f7fae · outbound

This paper cites ,[ˆP(M) t,n ]−1(ˆP(M) t,n (s(M) j,t |Z=z j)|Z=z) , where ˆP(i) t,n(·|Z) is the empirical CDF of S(i) t following the same definition as that in FLAP_M.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning ,[ˆP(M) t,n ]−1(ˆP(M) t,n (s(M) j,t |Z=z j)|Z=z) , where ˆP(i) t,n(·|Z) is the empirical CDF of S(i) t following the same definition as that in FLAP_M

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.778039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cc72fa4f-9a04-4e8b-b558-6fb13c6e12bf · outbound

This paper cites an unresolved cited work.

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-14T04:32:28.755885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2abffb74-8b83-4170-976b-e657d2f7e5e6 · outbound

This paper cites Implementation of CFSDP:Our implementation of CFSDP estimates the environment’s transition kernel using a neural network with hidden layers [64,64].

A Distribution Mapping Approach to Counterfactually Fair Reinforcement Learning Implementation of CFSDP:Our implementation of CFSDP estimates the environment’s transition kernel using a neural network with hidden layers [64,64]

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T04:32:28.729754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.