Paper Citation Record · LEDGER

Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.01345.

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

pith.paper-citation-record.v1
2402.01345 v6

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 2026-08-11T06:34:44.6726+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:52:09.245927Z

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

0
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 4cbfc9c8-3dcc-47e7-a5c3-c6f14c9970c8 · inbound

Hallucination of Multimodal Large Language Models: A Survey cites this paper.

Hallucination of Multimodal Large Language Models: A Survey Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:33:33.761667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 29fe357d-f98e-42da-8ccd-ca8ebc6b1c76 · inbound

Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key cites this paper.

Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T19:52:09.245927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c998b18e-4e50-4bca-b5b2-1741d40c3e0a · inbound

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink cites this paper.

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T14:29:27.963407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1df27a6f-b420-4e97-b4fa-da1772fae58d · inbound

Mitigating Object Hallucinations via Sentence-Level Early Intervention cites this paper.

Mitigating Object Hallucinations via Sentence-Level Early Intervention Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-25T08:35:32.665651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 19067ccb-f71f-4cb8-984f-b7ff2b8fd301 · inbound

OmniDPO: A Preference Optimization Framework to Address Omni-Modal Hallucination cites this paper.

OmniDPO: A Preference Optimization Framework to Address Omni-Modal Hallucination Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-05T13:22:21.210751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45bc690a-b722-41da-b9cc-53fd4fa111bd · inbound

Deep Pre-Alignment for VLMs cites this paper.

Deep Pre-Alignment for VLMs Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models

Reference 111

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:27:39.204170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.