Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Chaos persists in large-scale multi-agent learning despite adaptive learning rates
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.01032.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-30T03:56:08.162823Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T15:15:48.120003Z
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 ed19134b-2550-4bf5-8dc0-783272a0c9fa · inbound
Belief Engine: Configurable and Inspectable Stance Dynamics in Multi-Agent LLM Deliberation cites this paper.
Belief Engine: Configurable and Inspectable Stance Dynamics in Multi-Agent LLM Deliberation Chaos persists in large-scale multi-agent learning despite adaptive learning rates
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T16:02:38.966303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation a01015b7-f74e-4c31-9d3a-c1441a2fe556 · inbound
Risk-Sensitive Learning in Population Games under Extreme Events: Bifurcations and Chaotic Dynamics cites this paper.
Risk-Sensitive Learning in Population Games under Extreme Events: Bifurcations and Chaotic Dynamics Chaos persists in large-scale multi-agent learning despite adaptive learning rates
Reference 80
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T15:15:48.121873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.