Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1806.00553.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:52:58.625178Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T22:12:10.827156Z
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 be0bbd50-5ce7-4068-99d4-5cbbc999850d · inbound
ELEMENT: Episodic and Lifelong Exploration via Maximum Entropy cites this paper.
ELEMENT: Episodic and Lifelong Exploration via Maximum Entropy Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T22:12:10.832670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b502fdc2-64da-4b0c-ac3c-3dfdd09ef4db · inbound
Diverse Prompts: Illuminating the Prompt Space of Large Language Models with MAP-Elites cites this paper.
Diverse Prompts: Illuminating the Prompt Space of Large Language Models with MAP-Elites Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:52:58.625178Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.