Paper Citation Record · LEDGER

ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2411.15268.

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

pith.paper-citation-record.v1
2411.15268 v1

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 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:45:28.344201Z

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
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
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 ad860591-dd20-4f99-9944-9c9f1db318f6 · inbound

Seeing It or Not? Interpretable Vision-aware Latent Steering to Mitigate Object Hallucinations cites this paper.

Seeing It or Not? Interpretable Vision-aware Latent Steering to Mitigate Object Hallucinations ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:28.344201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8db010ab-6002-4ace-9595-504c9bfb64a9 · inbound

CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention cites this paper.

CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:22:38.778028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 472e75fd-80c5-4a34-abf7-c13dfc1fc7ab · inbound

GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs cites this paper.

GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T14:45:08.585297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6d4b064-def8-4da0-89ec-19ecbafe052f · inbound

Modality Bias in LVLMs: Analyzing and Mitigating Object Hallucination via Attention Lens cites this paper.

Modality Bias in LVLMs: Analyzing and Mitigating Object Hallucination via Attention Lens ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T05:04:21.748100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27d0bec9-0f49-4ce3-97e1-6ebb9e4e42ef · inbound

Can Large Multimodal Models Actively Recognize Faulty Inputs? A Systematic Evaluation Framework of Their Input Scrutiny Ability cites this paper.

Can Large Multimodal Models Actively Recognize Faulty Inputs? A Systematic Evaluation Framework of Their Input Scrutiny Ability ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T01:00:26.157643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e70b1380-311e-4d2d-bfc7-743dc351d180 · inbound

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering cites this paper.

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Reference 275

Resolution: verified exact; arxiv_id, observed 2026-05-09T23:54:45.848250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.