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Paper Citation Record · LEDGER

Learning to Sketch with Deep Q Networks and Demonstrated Strokes

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1810.05977.

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

pith.paper-citation-record.v1
1810.05977 v1

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:54:48.701444Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T14:57:58.195907Z

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 78ff1b41-e944-4978-a5d7-61c459f73875 · inbound

SketchAgent: Language-Driven Sequential Sketch Generation cites this paper.

SketchAgent: Language-Driven Sequential Sketch Generation Learning to Sketch with Deep Q Networks and Demonstrated Strokes

Reference 141

Resolution
unresolved
no resolver link, observed 2026-08-12T11:54:48.701444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:54:48.701444Z digest=sha256:8309c654947788a53055e1b608550426412921f280ab912ca58141df801da564

Observation 03ce2a9e-2bd1-4011-80a8-5f453fa1911e · inbound

MakeAnything: Harnessing Diffusion Transformers for Multi-Domain Procedural Sequence Generation cites this paper.

MakeAnything: Harnessing Diffusion Transformers for Multi-Domain Procedural Sequence Generation Learning to Sketch with Deep Q Networks and Demonstrated Strokes

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-09T14:57:58.201363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-09T14:57:58.152904Z digest=sha256:083fa95e6bdb8e99a053b7534f3ed2f36c8fa0c077eb083f78c42dc22b82532b