Paper Citation Record · LEDGER

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

As of 17 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 11 inbound Pith citation observations for arXiv:2502.06130.

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

pith.paper-citation-record.v1
2502.06130 v2

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:44:00.773941Z

measured 83 of 83 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:51:38.685943Z

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

72 of 72 outbound references displayed

verified exact0
verified fuzzy44
unresolved27
parse uncertain0
malformed identifier1
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 7db877c2-cdc7-4ab4-b7fe-784e658c3b8f · outbound

This paper cites write newline.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models write newline

Reference 1

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Source-reported events for the cited work

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Observation a0040755-0538-4056-a52f-583597614bf9 · outbound

This paper cites SegDiff: Image Segmentation with Diffusion Probabilistic Models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models SegDiff: Image Segmentation with Diffusion Probabilistic Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.556993Z

Source-reported events for the cited work

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Observation ec206db2-aec9-4037-b256-3688c6d940b5 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.561438Z

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Observation 97798ece-d41b-4e44-8b4a-442deab1e496 · outbound

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

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Hallucination of Multimodal Large Language Models: A Survey

Reference 4

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Observation 1aab79ab-6a0a-48c3-8e11-319de53e660b · outbound

This paper cites Muse: Text-to-image generation via masked generative transformers.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Muse: Text-to-image generation via masked generative transformers

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.654734Z

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Observation a9cd9d8c-a77e-4b6e-9864-b9be6388cdd4 · outbound

This paper cites Alleviating hallucinations in large vision-language models through hallucination-induced optimization.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Alleviating hallucinations in large vision-language models through hallucination-induced optimization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.645391Z

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Observation b3026656-c2f4-424e-b1ed-3b5f924ae8de · outbound

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

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

Reference 7

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Observation 1af4a25c-c05f-42a3-a8e5-5f75ff3fd62f · outbound

This paper cites Multi-object hallucination in vision language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Multi-object hallucination in vision language models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.635299Z

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Observation ef810f8e-451c-4897-beaf-05168cf996e3 · outbound

This paper cites HALC : Object hallucination reduction via adaptive focal-contrast decoding.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models HALC : Object hallucination reduction via adaptive focal-contrast decoding

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.625027Z

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Observation 1b6b05fa-1172-4f3b-8e90-2ca6cf147c20 · outbound

This paper cites Mitigating Hallucination in Visual Language Models with Visual Supervision.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Mitigating Hallucination in Visual Language Models with Visual Supervision

Reference 10

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Source-reported events for the cited work

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Observation 94182b5b-c08f-41e9-8b0b-43542756d8df · outbound

This paper cites Reproducible scaling laws for contrastive language-image learning.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Reproducible scaling laws for contrastive language-image learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.614431Z

Source-reported events for the cited work

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Observation b2e6c437-172a-4adf-95d8-723018aed653 · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Gonzalez, Ion Stoica, and Eric P

Reference 12

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Observation 03719736-3f43-46c2-9d6e-511e1bcc1f83 · outbound

This paper cites Palm: Scaling language modeling with pathways.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Palm: Scaling language modeling with pathways

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.598845Z

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Observation 5499fc33-cba0-4fc7-bce4-22578fc813cb · outbound

This paper cites Glass, and Pengcheng He.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Glass, and Pengcheng He

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.589133Z

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Observation e265d2c3-8ea0-4d93-935d-c514e7cbc907 · outbound

This paper cites Diffusion models in vision: A survey.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Diffusion models in vision: A survey

Reference 15

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Observation 731c4cbb-6938-4120-a50d-42eb869ba011 · outbound

This paper cites Instructblip: towards general-purpose vision-language models with instruction tuning.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Instructblip: towards general-purpose vision-language models with instruction tuning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.575892Z

Source-reported events for the cited work

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Observation 19836e82-2759-4388-8322-f5942fcc9886 · outbound

This paper cites Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding

Reference 17

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Observation fef21a7a-9306-4168-9871-f7c6e0c7f7f9 · outbound

This paper cites Multi-modal hallucination control by visual information grounding.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Multi-modal hallucination control by visual information grounding

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.566960Z

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Observation 11c6070d-9e78-446e-8b54-f4986b3bcf3e · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 19

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Observation ed094f39-52c1-4eba-a6ba-4ca8d837a8da · outbound

This paper cites Expressive text-to-image generation with rich text.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Expressive text-to-image generation with rich text

Reference 20

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Observation 80da1add-0d29-4791-b8ff-ea70e9661e4b · outbound

This paper cites Generative adversarial nets.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Generative adversarial nets

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.551459Z

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Observation f5b8216e-d83c-4f28-845e-465d9bb00404 · outbound

This paper cites Detecting and preventing hallucinations in large vision language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Detecting and preventing hallucinations in large vision language models

Reference 22

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Observation c536c0ce-5a29-4c20-a484-6dae53d2a0a8 · outbound

This paper cites Clipscore: A reference-free evaluation metric for image captioning.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Clipscore: A reference-free evaluation metric for image captioning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.533595Z

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Observation 9d4102d0-290c-44b0-a4af-fb0d090a926e · outbound

This paper cites Denoising diffusion probabilistic models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Denoising diffusion probabilistic models

Reference 24

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Observation c2f71472-851a-48ff-bde3-f0310ff4db3b · outbound

This paper cites Opera: Alleviating hallucination in multi-modal large language models via over-trust penalty and retrospection-allocation.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Opera: Alleviating hallucination in multi-modal large language models via over-trust penalty and retrospection-allocation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.519185Z

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Observation 7bfb7245-78c4-419a-830a-f6fd35471e82 · outbound

This paper cites Gqa: A new dataset for real-world visual reasoning and compositional question answering.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.508317Z

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Observation 91a6550e-513c-4888-a00f-c9acf6625cfd · outbound

This paper cites Hallucination augmented contrastive learning for multimodal large language model.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Hallucination augmented contrastive learning for multimodal large language model

Reference 27

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Observation 6ecfd414-2ba0-4de2-bf97-3d0dddc260f4 · outbound

This paper cites Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models

Reference 28

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Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Scaling up gans for text-to-image synthesis

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.489242Z

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This paper cites Elucidating the design space of diffusion-based generative models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Elucidating the design space of diffusion-based generative models

Reference 30

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This paper cites Code: Contrasting self-generated description to combat hallucination in large multi-modal models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Code: Contrasting self-generated description to combat hallucination in large multi-modal models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.474101Z

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Observation f67589ac-5cd7-48ed-b292-83f3a54c9b4e · outbound

This paper cites Mitigating object hallucinations in large vision-language models through visual contrastive decoding.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Mitigating object hallucinations in large vision-language models through visual contrastive decoding

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.463948Z

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Observation 35e16345-1cf2-475b-a8f7-6f86cce0ce29 · outbound

This paper cites Your diffusion model is secretly a zero-shot classifier.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Your diffusion model is secretly a zero-shot classifier

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.455305Z

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Observation 61a1908a-d05a-42fa-8c81-222842a53e02 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.447286Z

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Observation cf61d187-39b4-4030-b849-c2ee7d4d1510 · outbound

This paper cites Contrastive decoding: Open-ended text generation as optimization.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Contrastive decoding: Open-ended text generation as optimization

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.439454Z

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Observation eb582d46-4e34-4b48-a117-99f0261a5ce6 · outbound

This paper cites Evaluating object hallucination in large vision-language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Evaluating object hallucination in large vision-language models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.431640Z

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Observation 6e7569df-f61d-4b00-bda6-d8e456c67b8f · outbound

This paper cites Microsoft coco: Common objects in context.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Microsoft coco: Common objects in context

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.421091Z

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This paper cites Mitigating hallucination in large multi-modal models via robust instruction tuning.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Mitigating hallucination in large multi-modal models via robust instruction tuning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.410818Z

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Observation 320f0378-3f43-41b3-b916-19cae1108ee4 · outbound

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

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models A Survey on Hallucination in Large Vision-Language Models

Reference 39

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Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Visual instruction tuning

Reference 40

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Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Improved baselines with visual instruction tuning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.396292Z

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Observation 31cda4ef-7255-4a03-9cec-135c44d309ef · outbound

This paper cites Mmbench: Is your multi-modal model an all-around player? In European Conference on Computer Vision, pp.\ 216--233.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Mmbench: Is your multi-modal model an all-around player? In European Conference on Computer Vision, pp.\ 216--233

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.387590Z

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Observation 771650e1-2a63-4809-a255-8427601bd865 · outbound

This paper cites Glide: Towards photorealistic image generation and editing with text-guided diffusion models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Glide: Towards photorealistic image generation and editing with text-guided diffusion models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.378724Z

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Observation cb087075-3029-41a4-b132-915ce9d4639b · outbound

This paper cites SDXL : Improving latent diffusion models for high-resolution image synthesis.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models SDXL : Improving latent diffusion models for high-resolution image synthesis

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.369407Z

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Observation fbaacb01-9de3-4588-879c-0fb810ec4467 · outbound

This paper cites Object hallucination in image captioning.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Object hallucination in image captioning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.359473Z

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Observation 89340618-965f-48b1-bc79-e8f15b5eab85 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models High-resolution image synthesis with latent diffusion models

Reference 46

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This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Photorealistic text-to-image diffusion models with deep language understanding

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.691385Z

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This paper cites Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.341473Z

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Observation 0dfd7662-8d3a-45d8-a5a0-7616425fbbd8 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.697716Z

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Observation ff47aeb5-8b47-497c-9dae-12fea1f31023 · outbound

This paper cites A-okvqa: A benchmark for visual question answering using world knowledge.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models A-okvqa: A benchmark for visual question answering using world knowledge

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.326306Z

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Observation 12689926-7fe4-4249-8f5a-a5115c46c111 · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.703182Z

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Observation 47998742-14f3-44b3-b0a6-9bfcc2131023 · outbound

This paper cites Eyes wide shut? exploring the visual shortcomings of multimodal llms.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Eyes wide shut? exploring the visual shortcomings of multimodal llms

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.708416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d8ddb12-5a0b-4921-b8bf-e3663d1eee0f · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.711345Z

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Observation 708014e2-0402-4223-a07f-bc0f5ffd39fb · outbound

This paper cites Mitigating hallucinations in large vision-language models with instruction contrastive decoding.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Mitigating hallucinations in large vision-language models with instruction contrastive decoding

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.309670Z

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Observation 5eea5bfc-421a-4037-80bd-425a7bb145c5 · outbound

This paper cites Diffusion models for implicit image segmentation ensembles.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Diffusion models for implicit image segmentation ensembles

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.299229Z

Source-reported events for the cited work

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Observation c388cd21-0a60-467d-8f38-d6c238de53e6 · outbound

This paper cites RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.721183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b6ada38-ac89-44b1-8cbf-efbc8aa79369 · outbound

This paper cites Evaluating and analyzing relationship hallucinations in lvlms.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Evaluating and analyzing relationship hallucinations in lvlms

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.289929Z

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Observation 048481bf-088e-42a9-b747-36116b30c26e · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Diffusion models: A comprehensive survey of methods and applications

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.727907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17bde78e-0cc9-4bc2-98c5-dd7dfbd1bea1 · outbound

This paper cites mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.731303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57c92872-401b-4ee9-8e28-37f8045be344 · outbound

This paper cites Woodpecker: Hallucination Correction for Multimodal Large Language Models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Woodpecker: Hallucination Correction for Multimodal Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.734462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53ea1921-d351-4b43-94b7-39c03b3e9838 · outbound

This paper cites Scaling autoregressive models for content-rich text-to-image generation.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Scaling autoregressive models for content-rich text-to-image generation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.271751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 021f322e-0a72-4af9-86ca-9f8311d4e6be · outbound

This paper cites MM -vet: Evaluating large multimodal models for integrated capabilities.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models MM -vet: Evaluating large multimodal models for integrated capabilities

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.264173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 957ec9ed-d7bd-4db8-8e73-4c5863d75694 · outbound

This paper cites Less is more: Mitigating multimodal hallucination from an EOS decision perspective.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Less is more: Mitigating multimodal hallucination from an EOS decision perspective

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.255563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cdf92f3d-7837-4771-a7fc-fb9df41249a3 · outbound

This paper cites Multimodal image synthesis and editing: A survey and taxonomy.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Multimodal image synthesis and editing: A survey and taxonomy

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.246325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e95e7954-0c15-4053-b8e8-4d5d90e7774f · outbound

This paper cites Reflective instruction tuning: Mitigating hallucinations in large vision-language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Reflective instruction tuning: Mitigating hallucinations in large vision-language models

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.236346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a921a59b-2919-4be5-a373-c8aafe383fde · outbound

This paper cites Fact-and-reflection ( F a R ) improves confidence calibration of large language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Fact-and-reflection ( F a R ) improves confidence calibration of large language models

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.225942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 90c2a16c-4df1-480c-88ba-13e7215990dd · outbound

This paper cites Analyzing and mitigating object hallucination in large vision-language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Analyzing and mitigating object hallucination in large vision-language models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.215815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 41eb729b-11fd-489c-8a88-c45cf276d2c0 · outbound

This paper cites Mini GPT -4: Enhancing vision-language understanding with advanced large language models.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Mini GPT -4: Enhancing vision-language understanding with advanced large language models

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.206653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3fa799e2-f4df-4241-892d-0eab0f771d06 · outbound

This paper cites Dm-gan: Dynamic memory generative adversarial networks for text-to-image synthesis.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Dm-gan: Dynamic memory generative adversarial networks for text-to-image synthesis

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:44:01.196962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 88ec5a9b-6782-4ae0-aba6-94b8fd825f08 · outbound

This paper cites @esa (Ref.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models @esa (Ref

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.767233Z

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Unavailable: canonical work link unavailable.

Observation caa1733b-0062-4d2e-acf5-8851adac619d · outbound

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Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Unresolved cited work

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-08T16:44:00.771115Z

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Unavailable: canonical work link unavailable.

Observation c3f53df6-c17c-4d83-95c8-c0f4eca9a0bb · outbound

This paper cites an unresolved cited work.

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models Unresolved cited work

Reference 72

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Pith citing papers

Observation 8fbf3f47-e14b-4c3a-9ff6-02e9c2d5dd8e · inbound

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

Hallucination of Multimodal Large Language Models: A Survey Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 206

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:33:33.355426Z

Source-reported events for the cited work

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Observation 4cab3818-2559-4809-9ed5-14e1fc7b6856 · inbound

Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models cites this paper.

Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T20:51:38.685943Z

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Unavailable: canonical work link unavailable.

Observation a10d5500-02b9-4cc8-b43e-a2fbc8b451a7 · inbound

Controlling Multimodal LLMs via Reward-guided Decoding cites this paper.

Controlling Multimodal LLMs via Reward-guided Decoding Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 52

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Observation 159c0420-4dc4-4e6c-bd8d-dbef1ae14588 · inbound

Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation cites this paper.

Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 55

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Source-reported events for the cited work

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Observation f69f7d80-3727-4f49-b20e-2d7fb044997d · inbound

Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation cites this paper.

Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 161

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a5c88132-7129-46b9-9f38-6310f6739f5d · 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 Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 282

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T23:54:45.324151Z

Source-reported events for the cited work

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Observation b852acf4-b426-44d7-abcd-46de56601f94 · inbound

Uncertainty-Aware Exploratory Direct Preference Optimization for Multimodal Large Language Models cites this paper.

Uncertainty-Aware Exploratory Direct Preference Optimization for Multimodal Large Language Models Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:51:09.439758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e7205243-3903-4706-96c6-1dfcb0a82edf · inbound

Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding cites this paper.

Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T19:06:02.566245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 09666c7e-0248-4980-9cf1-b4f5b48fa0b6 · inbound

ADAPT: Attention Dynamics Alignment with Preference Tuning for Faithful MLLMs cites this paper.

ADAPT: Attention Dynamics Alignment with Preference Tuning for Faithful MLLMs Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:55:29.451277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation aa062bbb-00ab-4ac8-87ac-6ffb9b307a72 · inbound

DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models cites this paper.

DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-31T23:32:10.389429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8c614ac-b8ff-4999-82da-d0d1bcd75149 · inbound

Test-Time Hallucination Control in Large Vision-Language Models cites this paper.

Test-Time Hallucination Control in Large Vision-Language Models Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T14:19:24.819933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.