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Paper Citation Record · LEDGER

Mitigating Image Captioning Hallucinations in Vision-Language Models

As of 18 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2505.03420.

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

pith.paper-citation-record.v1
2505.03420 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:56:59.651886Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-14T19:18:41.987533Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T19:19:23.960000Z

Reference resolution

26 of 26 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9192742d-3976-4fbe-ab73-e28885520b77 · outbound

This paper cites Deep multimodal data fusion,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Deep multimodal data fusion,

Reference 1

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Source-reported events for the cited work

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Observation d5aa29a2-3f2a-4b68-8404-8675e139e461 · outbound

This paper cites A Survey on Hallucination in Large Vision-Language Models.

Mitigating Image Captioning Hallucinations in Vision-Language Models A Survey on Hallucination in Large Vision-Language Models

Reference 2

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Source-reported events for the cited work

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Observation 34d83191-f3c0-42d5-9360-26c34cb07cac · outbound

This paper cites Understanding and im- proving layer normalization,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Understanding and im- proving layer normalization,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9b92461d-49ae-4512-b422-22cb60193096 · outbound

This paper cites Miti- gating object hallucinations in large vision-language models through vi- sual contrastive decoding,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Miti- gating object hallucinations in large vision-language models through vi- sual contrastive decoding,

Reference 4

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Source-reported events for the cited work

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Observation 6f444e48-278a-4ee3-8657-e0798669ec31 · outbound

This paper cites Chatgpt (mar 14 version),.

Mitigating Image Captioning Hallucinations in Vision-Language Models Chatgpt (mar 14 version),

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3e9917c7-ff18-47a3-9391-07295bf406ed · outbound

This paper cites Gemini (dec 1 version),.

Mitigating Image Captioning Hallucinations in Vision-Language Models Gemini (dec 1 version),

Reference 6

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Source-reported events for the cited work

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Observation e31d3e08-dcf8-4f0d-8338-be19e0c43ba9 · outbound

This paper cites Visual instruction tuning,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Visual instruction tuning,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 29cbdcbe-db29-490d-80b9-d7b74546e00e · outbound

This paper cites Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey.

Mitigating Image Captioning Hallucinations in Vision-Language Models Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey

Reference 8

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Unavailable: canonical work link unavailable.

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Observation eb8593ea-9e9f-4365-948c-56daf9349773 · outbound

This paper cites Checkguard: Advancing stolen check detection with a cross-modal image-text bench- mark dataset,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Checkguard: Advancing stolen check detection with a cross-modal image-text bench- mark dataset,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3706723b-57a6-49dd-80e7-521b83e9937f · outbound

This paper cites Llava-next: Improved reasoning, ocr, and world knowledge,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Llava-next: Improved reasoning, ocr, and world knowledge,

Reference 10

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Source-reported events for the cited work

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Observation 7985b914-b4fc-415c-8710-8e6cbcf52fc6 · outbound

This paper cites InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks.

Mitigating Image Captioning Hallucinations in Vision-Language Models InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Reference 11

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Observation c3f7cc08-52dd-4edc-b6af-5d73a12415d9 · outbound

This paper cites Prismer: A Vision-Language Model with Multi-Task Experts.

Mitigating Image Captioning Hallucinations in Vision-Language Models Prismer: A Vision-Language Model with Multi-Task Experts

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation db143b52-2a62-4b9e-9754-a5f7f58e7ccf · outbound

This paper cites Detecting and Evaluating Medical Hallucinations in Large Vision Language Models.

Mitigating Image Captioning Hallucinations in Vision-Language Models Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

Reference 13

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Observation 87f8fbe4-685e-4e72-9017-5a9c1cf87f6f · outbound

This paper cites Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models.

Mitigating Image Captioning Hallucinations in Vision-Language Models Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models

Reference 14

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Source-reported events for the cited work

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Observation 41d52a2c-e9a5-4aab-8fd0-8d98ff9a5318 · outbound

This paper cites ClipCap: CLIP Prefix for Image Captioning.

Mitigating Image Captioning Hallucinations in Vision-Language Models ClipCap: CLIP Prefix for Image Captioning

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation da6123eb-4ac2-42c4-ba18-76a4564b578f · outbound

This paper cites Mitigating large vision- language model hallucination at post-hoc via multi-agent system,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Mitigating large vision- language model hallucination at post-hoc via multi-agent system,

Reference 16

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Source-reported events for the cited work

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Observation 68806463-f33a-43b8-b587-9650d5077bad · outbound

This paper cites Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback.

Mitigating Image Captioning Hallucinations in Vision-Language Models Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback

Reference 17

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Observation 51cf1c56-bb8c-457e-bb1a-9ea54c16cfda · outbound

This paper cites Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance.

Mitigating Image Captioning Hallucinations in Vision-Language Models Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance

Reference 18

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Observation aa4fce13-c512-4e9a-96e8-73f9169dcb6e · outbound

This paper cites Best-first beam search,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Best-first beam search,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0221d03e-0330-4ba7-8dd9-7e905a4a4143 · outbound

This paper cites Policy gradi- ent methods for reinforcement learning with function approximation,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Policy gradi- ent methods for reinforcement learning with function approximation,

Reference 20

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Observation 9f5770c2-cda7-4918-aa57-c8586404d700 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Learning transferable visual models from natural language supervision,

Reference 21

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Observation c0673f22-919b-43f4-afcb-e33adbc8a4b1 · outbound

This paper cites Attention is all you need,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Attention is all you need,

Reference 22

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Observation 001a194b-d610-423b-950a-c12364efba95 · outbound

This paper cites Facenet: A unified embed- ding for face recognition and clustering,.

Mitigating Image Captioning Hallucinations in Vision-Language Models Facenet: A unified embed- ding for face recognition and clustering,

Reference 23

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Observation 21735214-d299-4dc1-852b-bc675ad92b1a · outbound

This paper cites AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation.

Mitigating Image Captioning Hallucinations in Vision-Language Models AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Reference 24

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Observation 2f25cb7e-3f8f-464e-8e3b-b500674241fd · outbound

This paper cites From Pixels to Prose: A Large Dataset of Dense Image Captions.

Mitigating Image Captioning Hallucinations in Vision-Language Models From Pixels to Prose: A Large Dataset of Dense Image Captions

Reference 25

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Unavailable: canonical work link unavailable.

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Observation 2b9f4120-1c75-4397-9b33-e92dd12e1989 · outbound

This paper cites Llama 3.2 multimodal (version 2023),.

Mitigating Image Captioning Hallucinations in Vision-Language Models Llama 3.2 multimodal (version 2023),

Reference 26

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Source-reported events for the cited work

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Pith citing papers

Observation 1cc9f4ee-fb94-4a71-8c7b-05835ce49510 · inbound

Dual-Pathway Circuits of Object Hallucination in Vision-Language Models cites this paper.

Dual-Pathway Circuits of Object Hallucination in Vision-Language Models Mitigating Image Captioning Hallucinations in Vision-Language Models

Reference 38

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Source-reported events for the cited work

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