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Paper Citation Record · LEDGER

A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.11097.

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

pith.paper-citation-record.v1
2302.11097 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:22:41.682159Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T00:41:56.051676Z

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 883bd9c9-8ef6-468d-bce5-508d5b03e528 · inbound

Towards Geometry Problem Solving in the Large Model Era: A Survey cites this paper.

Towards Geometry Problem Solving in the Large Model Era: A Survey A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T11:22:41.682159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:22:41.682159Z digest=sha256:cb2519c6997f2bb5fce5b027a87be1fa46b73d718140cda37e1381f5f0cb67db

Observation cef20cfe-2727-4adc-b04f-e19bdd7459fb · inbound

GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines cites this paper.

GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-19T00:41:56.053944Z

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=2026-05-19T00:38:43.897231Z digest=sha256:384c79003968170272db7c24000fdabcaf1a862cc2aa81085f7099e12d287e07