Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:18:36.062787Z
Paper Citation Record · LEDGER
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network
As of 7 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 0 inbound Pith citation observations for arXiv:2505.19423.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
5 of 5 outbound references displayed
- verified exact0
- verified fuzzy2
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 7fc1e143-c7cc-404e-b83a-d3409d6cbd01 · outbound
This paper cites Progress in Aerospace Sciences 45 (2009), 50–79.
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network Progress in Aerospace Sciences 45 (2009), 50–79
Reference 2009
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:18:36.437433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 574f7523-9f0f-420b-88bd-f629066c739e · outbound
This paper cites OpenAI Gym.
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network OpenAI Gym
Reference 2016
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:18:35.690781Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3f6bbb5b-03dc-4294-b735-87e2dade3a72 · outbound
This paper cites Mastering Diverse Domains through World Models.
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network Mastering Diverse Domains through World Models
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:18:35.929808Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f3a4f8a4-78d4-46cb-947f-89d1e0d476d5 · outbound
This paper cites It's Morphing Time: Unleashing the Potential of Multiple LLMs via Multi-objective Optimization.
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network It's Morphing Time: Unleashing the Potential of Multiple LLMs via Multi-objective Optimization
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:18:36.062787Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90bcbd81-1738-4661-b88b-4e2d85ae6cce · outbound
This paper cites Artificial Intelligence (2025), 104308.
Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network Artificial Intelligence (2025), 104308
Reference 2025
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:18:36.749887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
No inbound Pith citation observations are available.