Pith. sign in

Paper Citation Record · LEDGER

Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1903.09338.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1903.09338 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T16:46:58.826849Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T18:40:03.504745Z

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 b340604d-c2f6-492f-8467-2aa743e5e90f · inbound

A Geometric Theory of Cognition for Machine Intelligence cites this paper.

A Geometric Theory of Cognition for Machine Intelligence Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-03T16:46:58.826849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:46:58.826849Z digest=sha256:bb4418b300c8d6d6a73f67cb7e49b24e9a82e098d2cbc54a84a5082cd2912853

Observation 500e94bc-9222-42aa-bcc2-2b9ae1d9076f · inbound

Explainable AI for Next-Generation Wireless Physical Layer: Basics, State-of-the-Art, and Open Challenges cites this paper.

Explainable AI for Next-Generation Wireless Physical Layer: Basics, State-of-the-Art, and Open Challenges Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-07-04T18:40:03.506346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-25T22:34:33.698421Z digest=sha256:80fc00e95060eaefa433d1c6d7ca659903288b3162c09adc9a7aaa21ed67d0f4