Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Deep Reinforcement Learning-Based Charging Scheduling Approach with Augmented Lagrangian for Electric Vehicle
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.09772.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T14:54:45.695265Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T00:09:15.014863Z
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 21e23f1e-5463-4152-bd56-f2d842482ba2 · inbound
Forecasting what Matters: Decision-Focused RL for Controlled EV Charging with Unknown Departure Times cites this paper.
Forecasting what Matters: Decision-Focused RL for Controlled EV Charging with Unknown Departure Times A Deep Reinforcement Learning-Based Charging Scheduling Approach with Augmented Lagrangian for Electric Vehicle
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T00:09:15.016676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 973562ae-c36e-45a9-abb8-e747f2898cda · inbound
Hierarchical Constrained Reinforcement Learning with Dynamic Boundary for Spatio-Temporal Vehicle-to-Grid Scheduling cites this paper.
Hierarchical Constrained Reinforcement Learning with Dynamic Boundary for Spatio-Temporal Vehicle-to-Grid Scheduling A Deep Reinforcement Learning-Based Charging Scheduling Approach with Augmented Lagrangian for Electric Vehicle
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:54:45.695265Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.