Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Spectral Decomposition Representation for Reinforcement Learning
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2208.09515.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:36:14.010039Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T14:58:33.275948Z
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 98a9d2b4-8fc7-4295-a270-9187317d309a · inbound
Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems cites this paper.
Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems Spectral Decomposition Representation for Reinforcement Learning
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:36:14.010039Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6295c50d-8ffc-42ef-bed6-8beab192319b · inbound
Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL cites this paper.
Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL Spectral Decomposition Representation for Reinforcement Learning
Reference 2014
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:16:40.943404Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8d1af092-0814-4b17-bc1a-aaf7e199f944 · inbound
Breaking the Computational Barrier: Provably Efficient Actor-Critic for Low-Rank MDPs cites this paper.
Breaking the Computational Barrier: Provably Efficient Actor-Critic for Low-Rank MDPs Spectral Decomposition Representation for Reinforcement Learning
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:46:05.411562Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation be83e757-bba4-4f27-a4d2-98ed9739e529 · inbound
Spectral Souping: A Unified Framework for Online Preference Alignment cites this paper.
Spectral Souping: A Unified Framework for Online Preference Alignment Spectral Decomposition Representation for Reinforcement Learning
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T07:59:50.995866Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a35147d8-0deb-4d17-8907-081682761fad · inbound
Learning to Adapt: Representation-Based Reinforcement Learning for Multi-Task Skill Transfer cites this paper.
Learning to Adapt: Representation-Based Reinforcement Learning for Multi-Task Skill Transfer Spectral Decomposition Representation for Reinforcement Learning
Reference 15
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T14:58:33.277368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.