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Paper Citation Record · LEDGER

Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning

As of 10 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.

pith.paper-citation-record.v1
2406.03234 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T19:24:48.899301Z

measured 0 of 1 external citation measurements

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T14:25:13.422578Z digest=sha256:f1ffd8874923d242fc643eaf8ca683d17985dfc0777e928277dd29115e41d886

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T10:10:21.427118Z digest=sha256:29a9767c7406f96f459bbe856b9f31ee3e58aadc4d0b19a683548629fe71c4f5

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.

source=arxiv_source observed=2026-07-11T19:24:48.899301Z digest=sha256:dbb67a5d9d062da21814d4d303d557ac1546d2adfc8324a6b702a23110113462