Paper Citation Record · LEDGER

Wasserstein Robust Reinforcement Learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1907.13196.

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

pith.paper-citation-record.v1
1907.13196 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:47:05.597189Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T12:06:03.897585Z

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 c41fbd83-e1e5-4e25-9a5d-aa8cfeb68377 · inbound

Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning cites this paper.

Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning Wasserstein Robust Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T19:08:00.342772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ab9bc6b-cab4-4dbc-b48b-8645b4b1b909 · inbound

Wasserstein Policy Optimization cites this paper.

Wasserstein Policy Optimization Wasserstein Robust Reinforcement Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T04:47:05.597189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 762dc1de-6b4f-49e3-8cab-a97687172f07 · inbound

Robust Adversarial Policy Optimization Under Dynamics Uncertainty cites this paper.

Robust Adversarial Policy Optimization Under Dynamics Uncertainty Wasserstein Robust Reinforcement Learning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:26:03.632733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c4782b70-83b6-42a7-9a89-09574af74b0b · inbound

Distributional Off-Policy Evaluation with Deep Quantile Process Regression cites this paper.

Distributional Off-Policy Evaluation with Deep Quantile Process Regression Wasserstein Robust Reinforcement Learning

Reference 162

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:06:03.902817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.