Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2411.13711.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T17:43:48.412070Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T23:22:46.684996Z
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 46969412-f26c-42cc-86e3-e8d8dc8a448a · inbound
From Set Convergence to Pointwise Convergence: Finite-Time Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes cites this paper.
From Set Convergence to Pointwise Convergence: Finite-Time Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T17:35:00.886167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 37d4a5d2-ea98-4e26-b95b-3f9da7b8d639 · inbound
Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise cites this paper.
Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
Reference 189
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T02:29:25.120406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 09600e6d-f149-4f19-8e66-c4adcce72e9a · inbound
Non-Asymptotic Convergence of Stochastic Iterative Algorithms: A Lyapunov Framework cites this paper.
Non-Asymptotic Convergence of Stochastic Iterative Algorithms: A Lyapunov Framework Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
Reference 96
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:12:46.708825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a2d748cd-b955-4d18-a041-7b23109f17d6 · inbound
Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo cites this paper.
Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
Reference 41
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-28T23:22:46.686693Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 71b9b92d-810f-49c1-8961-216e7c228253 · inbound
Concentration and Mean-Square Bounds for Contractive Stochastic Approximation: A Unified Elementary Approach cites this paper.
Concentration and Mean-Square Bounds for Contractive Stochastic Approximation: A Unified Elementary Approach Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T17:43:48.412070Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.