Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Neural PPO-Clip Attains Global Optimality: A Hinge Loss Perspective
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.13799.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-25T21:17:28.832301Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T19:30:07.606033Z
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 5500c30a-bf41-446d-8bfe-a68afde016f7 · inbound
Randomized Advantage Transformation (RAT): Computing Natural Policy Gradients via Direct Backpropagation cites this paper.
Randomized Advantage Transformation (RAT): Computing Natural Policy Gradients via Direct Backpropagation Neural PPO-Clip Attains Global Optimality: A Hinge Loss Perspective
Reference 135
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T12:48:17.561580Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fb52bd12-3557-4508-8120-10976269fba7 · inbound
Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning cites this paper.
Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Neural PPO-Clip Attains Global Optimality: A Hinge Loss Perspective
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T19:30:07.607563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.