Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2205.15512.
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 2026-08-15T20:21:29.794976Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T00:46:56.898522Z
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 382081da-3859-46bc-9a29-9abde3d635a0 · inbound
RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment cites this paper.
RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Reference 146
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T00:46:56.900693Z
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 6064c2ed-6b28-489a-8a2b-74a6bfba6e3b · inbound
On the Statistical Complexity for Offline and Low-Adaptive Reinforcement Learning with Structures cites this paper.
On the Statistical Complexity for Offline and Low-Adaptive Reinforcement Learning with Structures Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Reference 96
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:19:16.633815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec161056-9f73-4450-8caf-ccb1b88a4a80 · inbound
Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis cites this paper.
Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:21:29.794976Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30c3f43a-616f-48f8-8cfe-bfa15c203d48 · inbound
Fast Rates for Offline Contextual Bandits with Forward-KL Regularization under Single-Policy Concentrability cites this paper.
Fast Rates for Offline Contextual Bandits with Forward-KL Regularization under Single-Policy Concentrability Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T06:56:30.838377Z
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.