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Paper Citation Record · LEDGER

Categories of Semantic Concepts

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.10741.

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

pith.paper-citation-record.v1
2004.10741 v2

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:50:12.124626Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:50:14.636221Z

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 4bc963c8-e6ba-4d01-91b5-15408496ac15 · inbound

The Discovery Engine: A Framework for AI-Driven Synthesis and Navigation of Scientific Knowledge Landscapes cites this paper.

The Discovery Engine: A Framework for AI-Driven Synthesis and Navigation of Scientific Knowledge Landscapes Categories of Semantic Concepts

Reference 67

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:50:14.761586Z

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=2026-08-07T14:50:12.124626Z digest=sha256:f073af6cdeed75e32f6ca403e4eaa8d7c588c0249ab682569be4fe204b70bbe4

Observation 5dbac4df-afa0-41fe-ad65-fcdc17853668 · inbound

Compositional Semantic Communication for Physical AI: Category Theory Meets Game Theory cites this paper.

Compositional Semantic Communication for Physical AI: Category Theory Meets Game Theory Categories of Semantic Concepts

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-01T16:11:40.194663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:11:40.194663Z digest=sha256:57b185bbddc988a90ee37d9c5c7b4630a43ae04ae2013ebce2571206a06e0211