Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.03234.
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 2026-07-11T19:24:48.899301Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:17:57.432776Z
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 8713b231-5936-4ee6-94d2-38aefcfec4f1 · inbound
Consistency evaluation of benchmarks used for causal discovery cites this paper.
Consistency evaluation of benchmarks used for causal discovery Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T23:26:22.024183Z
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 f2ab46fc-b448-42d1-9d0a-9cff854520a8 · inbound
Learning Object Manipulation from Scratch via Contrastive Interaction cites this paper.
Learning Object Manipulation from Scratch via Contrastive Interaction Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:17:57.433993Z
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 ab34f7da-74cc-48ec-9a1a-75e6f5c7d6c3 · inbound
Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling cites this paper.
Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
Reference 147
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:24:48.899301Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.