Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2102.06548.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:45:55.405318Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T19:10:05.228039Z
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 f8309385-1e25-41c3-b22f-454f64601c69 · inbound
Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis cites this paper.
Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:45:55.405318Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23803ec9-8bf0-42d5-93ea-e8cd0227ca00 · inbound
A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging cites this paper.
A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:32:56.972939Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5cd57cd6-b470-4294-86a0-cbfe1e8326b1 · inbound
Minimax PAC Bounds for Learning in Exogenous Contextual MDPs cites this paper.
Minimax PAC Bounds for Learning in Exogenous Contextual MDPs Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T19:10:05.229713Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.