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Paper Citation Record · LEDGER

Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2107.07116.

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

pith.paper-citation-record.v1
2107.07116 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:38:00.498786Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T18:38:00.610120Z

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 6facfc28-7978-4fb0-9167-64dcde37d017 · inbound

Studying number theory with deep learning: a case study with the M\"obius and squarefree indicator functions cites this paper.

Studying number theory with deep learning: a case study with the M\"obius and squarefree indicator functions Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T18:38:00.629392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T18:38:00.498786Z digest=sha256:aec2ba6598ccc16c9393b1aaaf74f9b6d5bddb2ba79897fe5aab346a80222f32

Observation 6fde408f-20d1-4b0d-bcbe-70c25d904d04 · inbound

Learning Linear Temporal Specifications from Demonstrations with Uncertainty cites this paper.

Learning Linear Temporal Specifications from Demonstrations with Uncertainty Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-14T08:19:16.363607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T08:19:16.363607Z digest=sha256:b476606d017d9c81537f3731543a3384dc528d89c5ec9c88c6614b2f1a8c334d