Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Wasserstein Robust Reinforcement Learning
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1907.13196.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T19:08:00.342772Z
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 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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+00:00.