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Paper Citation Record · LEDGER

GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.10104.

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

pith.paper-citation-record.v1
2402.10104 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:16:57.983725Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T00:41:56.038854Z

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 2b655570-8226-4053-8528-253118b0354a · inbound

Large Language Models as Computable Approximations to Solomonoff Induction cites this paper.

Large Language Models as Computable Approximations to Solomonoff Induction GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:57.983725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:16:57.983725Z digest=sha256:19a9d0b0c4a492b3b807be8e53d2873b14b4527c9210c7687377948b39dda1ef

Observation 440473a2-487e-4a2d-9142-9c275c8f5343 · 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 GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T11:22:41.612534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:22:41.612534Z digest=sha256:c25568ea6ebc099a7cd594b3fe1ef3730464a0e48dd72ae53743096f93c9a9bb

Observation d3725ed5-4de1-4a98-bf60-d533f4279a6a · inbound

CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive Perspective cites this paper.

CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive Perspective GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T10:46:38.928978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:46:38.928978Z digest=sha256:87b3f89da0894aba9ab1024e4c69541503c1c6981bf5abff42de2004da79b11e

Observation 6bceaad6-cd75-4651-a292-1c826a2c4e8a · 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 GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-19T00:41:56.041632Z

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=sha256:07c69851a077e3576be2fdb1f602df0388abfb20604def01010472919743b0ac

Observation 7c0362ae-c44a-4f51-8df2-6bb4565b2277 · inbound

Boosting MLLM Spatial Reasoning with Geometrically Referenced 3D Scene Representations cites this paper.

Boosting MLLM Spatial Reasoning with Geometrically Referenced 3D Scene Representations GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:35:56.037889Z

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=2026-05-15T14:31:03.909336Z digest=sha256:e6f06f1b8f65bd80d1dfb67f7062c7cd06f15206b8da529a975bcc37227e19d5