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Paper Citation Record · LEDGER

LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2404.03118.

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

pith.paper-citation-record.v1
2404.03118 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:07:46.800582Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ee44eb31-a3c6-4da5-9756-b88ad0b6ba0b · inbound

Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question Answering cites this paper.

Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question Answering LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T19:10:15.506895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:10:15.506895Z digest=sha256:17b8cc36213b6888d48d997d74ae379fe7647484dcc9e269c1de76b7f80c6f53

Observation 918cbea9-5af6-48d8-8ab0-361f6fec4e68 · inbound

Cross-modal Information Flow in Multimodal Large Language Models cites this paper.

Cross-modal Information Flow in Multimodal Large Language Models LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T11:06:10.110272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:06:10.110272Z digest=sha256:535c057d0435b3376cca506719aa4d031524eb8ccca4aae1a67b2b1e42a7caa6

Observation 75fb7a60-d86c-4a4a-af98-8fc18add8f40 · inbound

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey cites this paper.

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 171

Resolution
unresolved
no resolver link, observed 2026-08-11T23:54:23.991410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:54:23.991410Z digest=sha256:4e1e9835ee6a4c66c5e860c1efac367dde04d29a19b9dec4fbb932e6f2b1a8db

Observation 5b9899bb-4eb7-4022-a506-2cbb82a0ec4e · inbound

SurgXBench: Explainable Vision-Language Model Benchmark for Surgery cites this paper.

SurgXBench: Explainable Vision-Language Model Benchmark for Surgery LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 26

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unresolved
no resolver link, observed 2026-08-15T21:07:46.800582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:07:46.800582Z digest=sha256:30f3a6f9f677d41f64c51b26967431735e5b8beeaefabe59d0e4b2ce1dd674f6

Observation 374baade-a7fc-4e4a-8609-d378d609dd23 · inbound

Backdoor Attack on Vision Language Models with Stealthy Semantic Manipulation cites this paper.

Backdoor Attack on Vision Language Models with Stealthy Semantic Manipulation LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T05:45:56.217075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:45:56.217075Z digest=sha256:e24f7566885fe46ec3a06eac0908fb6abcb948944a67a04b8c0b457005cce18a

Observation 5e4f2de0-b97d-40f0-980b-4e688a2f2045 · inbound

Adapting Lightweight Vision Language Models for Radiological Visual Question Answering cites this paper.

Adapting Lightweight Vision Language Models for Radiological Visual Question Answering LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T00:23:31.623245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:23:31.623245Z digest=sha256:f1e45fe157e0d6ecd872830ad465e7292c02f946cb2579634fab4042d7b61cb0

Observation 01581318-b063-4710-9727-44e317e01030 · inbound

GLIMPSE: Holistic Cross-Modal Explainability for Large Vision-Language Models cites this paper.

GLIMPSE: Holistic Cross-Modal Explainability for Large Vision-Language Models LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T18:46:03.733512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:46:03.733512Z digest=sha256:bd1893d9dfa9ba95851799240be7334673ef80d0712ac132bca4fc3765535029

Observation 3b7aa36e-fc2e-4ebc-8498-3307b4480735 · inbound

On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI cites this paper.

On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T10:22:23.245400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:22:23.245400Z digest=sha256:e7bdac3d429ecb2efd50cb6b1395ce4c705a4353ac2a01d30ed71c1900de73b1

Observation c567a3f9-b37f-4f23-a2e2-0a8a2046a310 · inbound

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs cites this paper.

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-21T19:54:20.301802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T19:51:04.983299Z digest=sha256:ebfd925c1c458ae7354f3b077d997f963561548df359a429ab416d9b2b11cc0b

Observation deb80ff8-176d-4eb8-b08c-f68889ec220d · inbound

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs cites this paper.

MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-03T21:44:01.801275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:44:01.801275Z digest=sha256:aec0bf1649f89d9970f01eae38ad8463b38a367b7378367b06886985b6f16f11

Observation c48dec0f-91e1-4384-89d2-17e5db212467 · inbound

Lifelong Learning in Vision-Language Models: Enhanced EWC with Cross-Modal Knowledge Retention cites this paper.

Lifelong Learning in Vision-Language Models: Enhanced EWC with Cross-Modal Knowledge Retention LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T19:52:52.607742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-14T19:49:38.046492Z digest=sha256:546c7d743c4e155bb5e9e49495bda2cf5e5018951a2e97ed4bc75cf0a1225b08

Observation 4b98a080-8713-42a6-8c7a-7920f24ea395 · inbound

The Case for Model Science: Verify, Explore, Steer, Refine cites this paper.

The Case for Model Science: Verify, Explore, Steer, Refine LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 210

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T17:32:24.972548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-28T17:24:32.311565Z digest=sha256:6f224e0e6af789085607571c7aca01f563be6d873eda0ea40fcfae49ba761ec0

Observation 830f7044-5311-48c7-b4a4-e492efe747ce · inbound

Multimodal Model Diffing for Feature Discovery and Control cites this paper.

Multimodal Model Diffing for Feature Discovery and Control LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:56.111721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:56.111721Z digest=sha256:55b1b59a431d86be9effeb5b44a41583e1659b75ca2061b76a8b0ff970ee7bfb