Paper Citation Record · LEDGER

Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2312.10160.

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

pith.paper-citation-record.v1
2312.10160 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T23:21:56.458813Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T03:55:59.684323Z

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 b7996512-1ca1-4b0c-aefc-b794b4230dbe · inbound

CodeMind: Evaluating Large Language Models for Code Reasoning cites this paper.

CodeMind: Evaluating Large Language Models for Code Reasoning Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-24T03:55:59.690061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 651b9185-9680-4781-b51a-9fc32e24c9cf · inbound

A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models cites this paper.

A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T23:21:56.458813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f91d606d-b81f-401c-861a-020c23f35c10 · inbound

ChartCap: Mitigating Hallucination of Dense Chart Captioning cites this paper.

ChartCap: Mitigating Hallucination of Dense Chart Captioning Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T04:43:34.929204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5403e4a4-25aa-4cb0-b278-de929c8dd958 · inbound

Adaptive Sparse Softmax: An Effective and Efficient Softmax Variant cites this paper.

Adaptive Sparse Softmax: An Effective and Efficient Softmax Variant Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T04:41:37.953039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa15ddd0-733f-4020-a8fd-3e2b20c2a241 · inbound

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models cites this paper.

Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:00:57.179242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 25d3b808-e9c1-4005-9acc-393b78017e8b · inbound

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-03T08:15:20.174632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.