Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Hypernetwork-based approach for optimal composition design in partially controlled multi-agent systems
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.12605.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-14T20:40:32.584469Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T20:42:58.021948Z
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 1d79693d-349f-4e96-9ba2-a4a7ce62a4ad · inbound
Events as Triggers for Behavioral Diversity in Multi-Agent Reinforcement Learning cites this paper.
Events as Triggers for Behavioral Diversity in Multi-Agent Reinforcement Learning Hypernetwork-based approach for optimal composition design in partially controlled multi-agent systems
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T03:52:12.496910Z
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.
Observation 430285bb-3139-456f-9974-385b59bb1448 · inbound
Events as Triggers for Behavioral Diversity in Multi-Agent Reinforcement Learning cites this paper.
Events as Triggers for Behavioral Diversity in Multi-Agent Reinforcement Learning Hypernetwork-based approach for optimal composition design in partially controlled multi-agent systems
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T20:42:58.025704Z
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.