Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Lipschitz Continuity in Model-based Reinforcement Learning
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1804.07193.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T04:59:29.778982Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-17T12:04:10.871465Z
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 b542f905-588d-4e63-a3f4-a60e5c47e78c · inbound
Training Language Models to Self-Correct via Reinforcement Learning cites this paper.
Training Language Models to Self-Correct via Reinforcement Learning Lipschitz Continuity in Model-based Reinforcement Learning
Reference 295
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-17T12:04:10.873417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 22af8a4b-41b4-401c-b211-b638843799b6 · inbound
Bellman operator convergence enhancements in reinforcement learning algorithms cites this paper.
Bellman operator convergence enhancements in reinforcement learning algorithms Lipschitz Continuity in Model-based Reinforcement Learning
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:36:21.402923Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bc17e08a-d9e3-4061-b923-471599a71ac0 · inbound
Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction cites this paper.
Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Lipschitz Continuity in Model-based Reinforcement Learning
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T04:59:29.778982Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.