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Paper Citation Record · LEDGER

Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network

As of 20 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.

pith.paper-citation-record.v1
2505.19423 v2

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:18:36.062787Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:18:35.823328Z digest=sha256:6ad551463774fc63fa079dcfe953280b4f5641b23a9e5ba7284ee036cc1d9f49

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.

source=pdf_text observed=2026-08-07T14:18:35.690781Z digest=sha256:18400cb07e3028608a7b165c20e86d27bae9ec545f9c111c05be6cf8927cb243

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.

source=pdf_text observed=2026-08-07T14:18:35.929808Z digest=sha256:83c0e4b88cdd2d069320d195c1d9471cc94190882d5a061a4c965247ba6e8dc1

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.

source=pdf_text observed=2026-08-07T14:18:36.062787Z digest=sha256:d0d26d80ff457ba4153c08f892d40bdca0e38f608a4fd0c77d042ac54ba146c8

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:18:35.587860Z digest=sha256:62c3d15b2ee365e94e1cba53010a947e3fda18b0865411cea6abbb5a5170bc47

Pith citing papers

No inbound Pith citation observations are available.