Paper Citation Record · LEDGER

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features

As of 8 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2509.08266.

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

pith.paper-citation-record.v1
2509.08266 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T20:58:26.760637Z

measured 25 of 25 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

verified exact0
verified fuzzy12
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8bbe823e-462c-40e3-b69f-d81d2a79d9d7 · outbound

This paper cites Vision Language Models are Biased.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Vision Language Models are Biased

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:24.320688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 401146e2-0882-438c-8edd-f1ed24fb398a · outbound

This paper cites Open ai: Introducing openai o3 and o4-mini, 2025.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Open ai: Introducing openai o3 and o4-mini, 2025

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:30.323971Z

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.

Observation 5a50d699-9317-403e-b6f0-fa7c18a6eef9 · outbound

This paper cites Google deepmind: Gemini 2.5 pro, 2025.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Google deepmind: Gemini 2.5 pro, 2025

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:30.136766Z

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.

Observation 9f01fb84-53a7-4d57-8174-b08f4d95fdad · outbound

This paper cites Do Vision-Language Models Really Understand Visual Language?.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Do Vision-Language Models Really Understand Visual Language?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:24.649412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42696a3c-e460-4e02-b84b-5a5fa5eeee81 · outbound

This paper cites VLind-Bench: Measuring Language Priors in Large Vision-Language Models.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features VLind-Bench: Measuring Language Priors in Large Vision-Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:24.757401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a831130e-7f07-4a94-b749-20bb5a609c37 · outbound

This paper cites Vhelm: A holistic evaluation of vision language models.Advances in Neural Information Processing Systems, 37:140632–140666, 2024.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Vhelm: A holistic evaluation of vision language models.Advances in Neural Information Processing Systems, 37:140632–140666, 2024

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:29.845483Z

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.

Observation 6d34adfe-0899-4e2c-9216-88ccf8b798d7 · outbound

This paper cites Probing the Visualization Literacy of Vision Language Models: the Good, the Bad, and the Ugly.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Probing the Visualization Literacy of Vision Language Models: the Good, the Bad, and the Ugly

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:24.989862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15927bdb-d807-466a-911a-3ca3587833fb · outbound

This paper cites Don't Miss the Forest for the Trees: Attentional Vision Calibration for Large Vision Language Models.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Don't Miss the Forest for the Trees: Attentional Vision Calibration for Large Vision Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:25.135570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b317174-849f-4293-b417-c7c08d6f86af · outbound

This paper cites Mitigating object hallucinations in large vision-language models with assembly of global and local attention.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Mitigating object hallucinations in large vision-language models with assembly of global and local attention

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:29.632342Z

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.

Observation 65ddff21-ce30-45c1-9483-4fd7cbd0887b · outbound

This paper cites See What You Are Told: Visual Attention Sink in Large Multimodal Models.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features See What You Are Told: Visual Attention Sink in Large Multimodal Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:25.290792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 088d296f-b968-48ad-bad2-d164b2ac3698 · outbound

This paper cites Qwen2.5-vl, January 2025.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Qwen2.5-vl, January 2025

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:25.372227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d57f32d-4e42-4dd6-a132-2d26bd3076d7 · outbound

This paper cites Kimi-VL Technical Report.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Kimi-VL Technical Report

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T20:58:25.467092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dae0dc1-d113-46ce-93d8-f074cc831067 · outbound

This paper cites an unresolved cited work.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-04T20:58:29.516499Z

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.

Observation 82fc1942-6ff6-48f2-a64b-25d2d07aeddf · outbound

This paper cites an unresolved cited work.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-04T20:58:29.272055Z

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.

Observation df664d15-dfa3-41ba-8c56-15d0995bc94c · outbound

This paper cites an unresolved cited work.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-04T20:58:29.061393Z

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.

Observation 112c2379-fe21-4f38-97ed-77e6e4658966 · outbound

This paper cites an unresolved cited work.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-04T20:58:28.837798Z

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.

Observation f2bc3755-82a8-4d66-a4b7-cf976b1af856 · outbound

This paper cites We report these metrics over Qwen2.5-VL-7B, Qwen2.5-VL-32B and Kimi-VL-A3B.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features We report these metrics over Qwen2.5-VL-7B, Qwen2.5-VL-32B and Kimi-VL-A3B

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:28.617063Z

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.

Observation 1ed5b933-1c0a-4ca8-8453-642c384360be · outbound

This paper cites In Flag Stars, specifying the target object and requiring structured output substantially increases accuracy (up to 0.4; Figures 8 and 9).

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features In Flag Stars, specifying the target object and requiring structured output substantially increases accuracy (up to 0.4; Figures 8 and 9)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:28.422583Z

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.

Observation d64897c2-e6a6-488a-b583-2d0ead436151 · outbound

This paper cites Refer Figures 5,6 and 7.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Refer Figures 5,6 and 7

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:28.218182Z

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.

Observation 28fd5db4-1fd8-465e-bdae-e4042f821720 · outbound

This paper cites We can see that the proportion of attention across the same prompt for different object shapes are within a very small interval.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features We can see that the proportion of attention across the same prompt for different object shapes are within a very small interval

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:27.939333Z

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.

Observation 5dd5e933-aa7c-4eab-b042-7da77c559e15 · outbound

This paper cites When the number of objects in the image is <10, the models perform relatively accurately, but counting performance becomes less accurate as we move towards the >40 bucket.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features When the number of objects in the image is <10, the models perform relatively accurately, but counting performance becomes less accurate as we move towards the >40 bucket

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:27.748866Z

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.

Observation eee89944-913f-45a8-8018-bd2c559f5bac · outbound

This paper cites Errors for Qwen 2.5-VL are centered mostly around negative values, meaning the model often underestimates compared to ground truth.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Errors for Qwen 2.5-VL are centered mostly around negative values, meaning the model often underestimates compared to ground truth

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:27.549741Z

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.

Observation 8d70d92a-852e-4597-b085-c4614e156384 · outbound

This paper cites Refer Figures 8 and 9.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Refer Figures 8 and 9

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:27.330933Z

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.

Observation 675d7e65-d541-4b06-a7be-441f0b0639a3 · outbound

This paper cites an unresolved cited work.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-04T20:58:27.138585Z

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.

Observation 0ffc17cc-26f5-4d94-80b4-55c3c9bb822f · outbound

This paper cites [1], when using the same prompts and data as them.

Examining Vision Language Models through Multi-dimensional Experiments with Vision and Text Features [1], when using the same prompts and data as them

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T20:58:27.003109Z

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.

Pith citing papers

No inbound Pith citation observations are available.