Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2311.06210.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:34:44.958023Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T14:29:08.866393Z
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 bf4a7aca-b7d9-4bdf-874d-60d88e9f27d5 · inbound
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework cites this paper.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:34:32.352464Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf4e7fb9-0bb7-4518-9214-8d04b84de3d4 · inbound
Coordinating the Unknown Lipschitz Constant in Multiplayer Bandits cites this paper.
Coordinating the Unknown Lipschitz Constant in Multiplayer Bandits Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:31:10.488840Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7b1c62e-4526-43b8-8f8e-5e3286f00657 · inbound
Robust Multi-Agent Bandits with Heavy-Tailed Rewards and Information Asymmetry cites this paper.
Robust Multi-Agent Bandits with Heavy-Tailed Rewards and Information Asymmetry Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:29:08.873684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4936443f-d52f-419d-880c-eb85a42ea507 · inbound
DCM Bandits: Multiplayer Information Asymmetric Cascading Bandits for Multiple Clicks cites this paper.
DCM Bandits: Multiplayer Information Asymmetric Cascading Bandits for Multiple Clicks Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:34:44.958023Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e5c7185-99ba-44e1-8684-5d060dfbaf9c · inbound
Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry cites this paper.
Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:06:35.401617Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.