Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Causal Reinforcement Learning using Observational and Interventional Data
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2106.14421.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:59:58.688564Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T14:38:21.507414Z
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 2e900c3b-ea99-414a-b1a4-2fd7bfad1715 · inbound
Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges cites this paper.
Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges Causal Reinforcement Learning using Observational and Interventional Data
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:59:58.688564Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1f92949-86b9-4f77-a06d-bd27200a5fad · inbound
Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations cites this paper.
Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations Causal Reinforcement Learning using Observational and Interventional Data
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:56:57.491677Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 994009b3-bc32-46ae-8f06-a0b407caab63 · inbound
Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety cites this paper.
Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety Causal Reinforcement Learning using Observational and Interventional Data
Reference 108
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T14:38:21.508952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1e95bc7b-7423-4b35-9495-837fad30070c · inbound
CRRL: A Causality-Based Reinforcement Learning Framework for Autonomous System Recovery cites this paper.
CRRL: A Causality-Based Reinforcement Learning Framework for Autonomous System Recovery Causal Reinforcement Learning using Observational and Interventional Data
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T04:20:13.776011Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a12516e9-83ea-4713-a526-21d054f5a053 · inbound
Property-driven Causal Abstractions for Markov Decision Processes cites this paper.
Property-driven Causal Abstractions for Markov Decision Processes Causal Reinforcement Learning using Observational and Interventional Data
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T21:09:38.034606Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.