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Paper Citation Record · LEDGER

Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1804.06516.

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

pith.paper-citation-record.v1
1804.06516 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T11:28:56.883342Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T11:30:42.351897Z

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 155960db-4180-4e24-a09c-c14e507bd082 · inbound

Improving Performance of End-to-End ASR on Numeric Sequences cites this paper.

Improving Performance of End-to-End ASR on Numeric Sequences Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-25T11:30:42.357308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T11:28:56.883342Z digest=sha256:23ef0941a5b7fa0c6a8c0cd58ceda156893335b6f1612d04a873785ad6f9e6ae