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Paper Citation Record · LEDGER

Can Large Language Models Understand Symbolic Graphics Programs?

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.08313.

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

pith.paper-citation-record.v1
2408.08313 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:11:54.640127Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T15:48:35.116154Z

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 4d440b79-4e4e-4ff3-a526-362cabbd71c8 · inbound

SVGenius: Benchmarking LLMs in SVG Understanding, Editing and Generation cites this paper.

SVGenius: Benchmarking LLMs in SVG Understanding, Editing and Generation Can Large Language Models Understand Symbolic Graphics Programs?

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T11:11:54.640127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:11:54.640127Z digest=sha256:3ab918d0f14bde8270c2abb7512a668b96dd1e403bd13cb0f233903aa5c33b65

Observation e5896bee-77f4-446b-a0f0-1376834f7baa · inbound

Answer-Centric or Reasoning-Driven? Uncovering the Latent Memory Anchor in LLMs cites this paper.

Answer-Centric or Reasoning-Driven? Uncovering the Latent Memory Anchor in LLMs Can Large Language Models Understand Symbolic Graphics Programs?

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T23:33:55.776114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:33:55.776114Z digest=sha256:929d5805421e663c07347a11b4531214deed54d7cb31262238122f950be7f4d4

Observation 3da0100f-2fca-47a0-9b8e-424868692dbc · inbound

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency cites this paper.

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency Can Large Language Models Understand Symbolic Graphics Programs?

Reference 102

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:58:59.239889Z

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=2026-05-10T11:58:58.660564Z digest=sha256:de7ad7a3361de53f4575a36d9c7df3fdab612bd9456ba8082565c68b9c259772

Observation e04dd7be-5a97-47a0-89e2-8817289af4fd · inbound

BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning cites this paper.

BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning Can Large Language Models Understand Symbolic Graphics Programs?

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-02T20:55:10.004501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:55:10.004501Z digest=sha256:b57c6d44fbf8c4e841c437c81b4c787860455d54131bed6f0e519d82e8b01081

Observation 40711a87-a2a8-4f7b-b9c1-faefd8536faa · inbound

CodePercept: Code-Grounded Visual STEM Perception for MLLMs cites this paper.

CodePercept: Code-Grounded Visual STEM Perception for MLLMs Can Large Language Models Understand Symbolic Graphics Programs?

Reference 35

Resolution
unresolved
no resolver link, observed 2026-07-14T23:22:13.847876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T23:22:13.847876Z digest=sha256:9af98e8b90a4f121cf959064200ef6dc9613c5e52539b6dd90d420b77efc0a95

Observation 72f681d8-204c-45a0-b9aa-4e86fa404f4b · inbound

mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval cites this paper.

mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval Can Large Language Models Understand Symbolic Graphics Programs?

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:51:46.501995Z

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=2026-05-10T06:46:40.040113Z digest=sha256:bc435bb18ad2714abafb1e8d8590fcd9638342b003b89a3c5e243f4423d73da2

Observation 58b1db78-6914-4ab2-bc87-f59313bc2305 · inbound

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing cites this paper.

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing Can Large Language Models Understand Symbolic Graphics Programs?

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-03T15:48:35.117528Z

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=2026-07-03T15:38:36.388570Z digest=sha256:2d1ead23d1355f3b39402a33d85843811abd9a66d6b94966f1f4758a27f4c5ee