Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1710.06117.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T10:11:03.735843Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:49:31.325298Z
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 94428f90-9027-4148-a7a8-3af780688538 · inbound
UMC: Unified Resilient Controller for Legged Robots with Joint Malfunctions cites this paper.
UMC: Unified Resilient Controller for Legged Robots with Joint Malfunctions Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T10:11:03.735843Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84092647-64b7-436b-9877-aa5646af6a4e · inbound
CoMoCAVs: Cohesive Decision-Guided Motion Planning for Connected and Autonomous Vehicles with Multi-Policy Reinforcement Learning cites this paper.
CoMoCAVs: Cohesive Decision-Guided Motion Planning for Connected and Autonomous Vehicles with Multi-Policy Reinforcement Learning Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:49:31.373279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.