Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2301.05334.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:48:17.832337Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T16:23:39.682751Z
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 e6a32de1-4fab-4249-9f6e-12534fc2fd1e · inbound
Asynchronous Cooperative Multi-Agent Reinforcement Learning with Limited Communication cites this paper.
Asynchronous Cooperative Multi-Agent Reinforcement Learning with Limited Communication TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T03:35:20.728168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 4fe27134-b04e-45e8-9654-655a59bd277b · inbound
Application of LLMs to Multi-Robot Path Planning and Task Allocation cites this paper.
Application of LLMs to Multi-Robot Path Planning and Task Allocation TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:48:17.832337Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b624126-07e8-46a3-a810-02aabf12244e · inbound
Transformer-Enhanced Reinforcement Learning: Fundamentals and Applications in Communication Networks cites this paper.
Transformer-Enhanced Reinforcement Learning: Fundamentals and Applications in Communication Networks TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T16:23:39.684176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.