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VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task

As of 9 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2511.13420.

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Coverage vector

measured 53 of 53 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-03T21:51:15.592797Z

measured 53 of 53 standing notices

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measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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53 of 53 outbound references displayed

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Outbound references

Observation 914ac88a-3798-4196-8ce5-1bd65f7797b8 · outbound

This paper cites GPT-4 Technical Report.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task GPT-4 Technical Report

Reference 1

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Observation a1268171-17a2-47ce-9580-905110224168 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

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Observation 7db8b67d-9ab5-4fe0-9e81-643973cc6272 · outbound

This paper cites Ict: Image-object cross-level trusted intervention for mitigating object halluci- nation in large vision-language models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Ict: Image-object cross-level trusted intervention for mitigating object halluci- nation in large vision-language models

Reference 3

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Observation 7d9ba064-572c-47a0-9695-0b510ad9b294 · outbound

This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 4

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Observation acd6cde2-e6f6-4313-b20f-22826c01b89d · outbound

This paper cites Halc: Object hallucination reduc- tion via adaptive focal-contrast decoding.Int.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Halc: Object hallucination reduc- tion via adaptive focal-contrast decoding.Int

Reference 5

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Observation d964d2ca-45f2-48dc-8cc1-95d9ab4c83f9 · outbound

This paper cites Dola: Decoding by con- trasting layers improves factuality in large language models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Dola: Decoding by con- trasting layers improves factuality in large language models

Reference 6

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Observation a64bd5e2-2236-435f-98fc-e65ffd753ef7 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Instructblip: Towards general- purpose vision-language models with instruction tuning,

Reference 7

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Observation a5b798ab-4ce6-458d-a9ba-d351b95c24a5 · outbound

This paper cites Deepseek-r1: Incentivizing reasoning capa- bility in llms via reinforcement learning, 2025.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Deepseek-r1: Incentivizing reasoning capa- bility in llms via reinforcement learning, 2025

Reference 8

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Observation 43c2b204-b7bd-4148-9669-48b105e1e128 · outbound

This paper cites Truthprint: Mitigating large vision- language models object hallucination via latent truthful- guided pre-intervention.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Truthprint: Mitigating large vision- language models object hallucination via latent truthful- guided pre-intervention

Reference 9

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Observation e38ac6f2-9ed6-4fe3-8833-5a820d0cc6fa · outbound

This paper cites Creation-mmbench: Assessing context-aware creative intelligence in mllm.IEEE Int.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Creation-mmbench: Assessing context-aware creative intelligence in mllm.IEEE Int

Reference 10

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Observation b20b2fd9-6ffb-4420-9bca-1ae17b785968 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Multi-modal hal- lucination control by visual information grounding

Reference 11

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Observation 14cb3692-2135-4182-a230-b434072198b8 · outbound

This paper cites The Llama 3 Herd of Models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task The Llama 3 Herd of Models

Reference 12

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Observation b4a4fead-29b8-43d0-9fd5-db859e498546 · outbound

This paper cites Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models

Reference 13

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Observation 3648b5b1-0712-429b-bdf1-59508e25bdb5 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Detecting and preventing hallucinations in large vision language models

Reference 14

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Observation 6d2938b5-a067-4e67-9e0a-5696831d646c · outbound

This paper cites CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning

Reference 15

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Observation 30be580b-45d0-4066-b425-912e764468c7 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Opera: Alleviating hallucination in multi- modal large language models via over-trust penalty and retrospection-allocation

Reference 16

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Observation 0e7a72c3-208a-464e-b27d-f458473e1f77 · outbound

This paper cites Devils in middle layers of large vision- language models: Interpreting, detecting and mitigating ob- ject hallucinations via attention lens.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Devils in middle layers of large vision- language models: Interpreting, detecting and mitigating ob- ject hallucinations via attention lens

Reference 17

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Observation c700600b-32a7-46d3-b562-e1a203454bb2 · outbound

This paper cites Faith- score: Fine-grained evaluations of hallucinations in large vision-language models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Faith- score: Fine-grained evaluations of hallucinations in large vision-language models

Reference 18

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Observation 9eb694af-ecb8-4a1d-9185-395bb681638d · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Mitigating object hal- lucinations in large vision-language models through visual contrastive decoding

Reference 19

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Observation 84164d1b-748c-4a5c-97b9-99c739743be6 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Evaluating object hallucination in large vision-language models.Conf

Reference 20

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Observation 30efe728-7f57-4d94-b79d-bf4d73e978e7 · outbound

This paper cites Lawrence Zitnick, and Piotr Doll ´ar.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Lawrence Zitnick, and Piotr Doll ´ar

Reference 21

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Observation 2b97f0c0-a555-4edc-843b-d1ab36c141d0 · outbound

This paper cites The brain’s voices: comparing nonclinical auditory hal- lucinations and imagery.Cerebral Cortex, 21(2):330–337,.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task The brain’s voices: comparing nonclinical auditory hal- lucinations and imagery.Cerebral Cortex, 21(2):330–337,

Reference 22

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Observation 80222fd2-f5fc-447e-98ef-3286c07ac961 · outbound

This paper cites Visual instruction tuning.Adv.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Visual instruction tuning.Adv

Reference 23

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Observation 70818bbe-9a44-47c0-ae0e-8e1f0800bae3 · outbound

This paper cites Improved baselines with visual instruction tuning.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Improved baselines with visual instruction tuning

Reference 24

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Observation 498fe422-af35-47d8-938c-6efd7cd88594 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task A Survey on Hallucination in Large Vision-Language Models

Reference 25

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Observation 314d73ab-7e64-4e49-b6fa-734184f07266 · outbound

This paper cites Phd: A chatgpt-prompted visual hallucination evaluation dataset.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Phd: A chatgpt-prompted visual hallucination evaluation dataset

Reference 26

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Observation eef333d0-bc37-4c38-8a50-5614c56c4811 · outbound

This paper cites Reduc- ing hallucinations in vision-language models via latent space steering.Int.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Reduc- ing hallucinations in vision-language models via latent space steering.Int

Reference 27

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Observation e27106d2-f8fe-4ce2-8d49-8cad5f42bf40 · outbound

This paper cites Mitigating hallucination through theory-consistent symmetric multimodal preference optimization.Adv.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Mitigating hallucination through theory-consistent symmetric multimodal preference optimization.Adv

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Observation 5a7cda37-44cd-4815-9aff-8623197927bb · outbound

This paper cites Negative object presence evaluation (nope) to measure object hallucination in vision-language models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Negative object presence evaluation (nope) to measure object hallucination in vision-language models

Reference 29

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Observation a50d4658-cd75-42c3-94c3-8a0d4801045b · outbound

This paper cites A Character-Centric Creative Story Generation via Imagination.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task A Character-Centric Creative Story Generation via Imagination

Reference 30

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Observation f896a429-8e58-43c6-8943-235d50cfddb8 · outbound

This paper cites Second: Mitigating perceptual hallucination in vision- language models via selective and contrastive decoding.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Second: Mitigating perceptual hallucination in vision- language models via selective and contrastive decoding

Reference 31

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Observation d519c40d-3bb2-4149-bb48-f22a84b12065 · outbound

This paper cites Mitigating object hallucinations via sentence-level early in- tervention.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Mitigating object hallucinations via sentence-level early in- tervention

Reference 32

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Observation 6eb6875f-8099-4231-8168-2760ad31681d · outbound

This paper cites Intervene-all-paths: Unified mitigation of lvlm hallucina- tions across alignment formats.Adv.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Intervene-all-paths: Unified mitigation of lvlm hallucina- tions across alignment formats.Adv

Reference 33

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Observation 4fcdcf09-fadd-4a00-87a9-66c1ef28256a · outbound

This paper cites Object hallucination in im- age captioning.Conf.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Object hallucination in im- age captioning.Conf

Reference 34

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Observation a9c15cba-049b-4237-9710-4ca6babdc3eb · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Aligning Large Multimodal Models with Factually Augmented RLHF

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Observation 4d2ee0c6-4b2f-46c2-b8f1-f314fd12eb88 · outbound

This paper cites Octopus: Alleviating hal- lucination via dynamic contrastive decoding.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Octopus: Alleviating hal- lucination via dynamic contrastive decoding

Reference 36

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Observation e6ec0456-7f81-460b-8243-1419319b0f47 · outbound

This paper cites Seeing far and clearly: Mitigat- ing hallucinations in mllms with attention causal decoding.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Seeing far and clearly: Mitigat- ing hallucinations in mllms with attention causal decoding

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source=pdf_text observed=2026-08-03T21:51:15.530649Z digest=sha256:b2bc657ef6230566c22aeb4432f543b2c2a37cc56860a94d57fcc0cbb52c74fe

Observation a5f8d336-f52c-4bea-92b8-df256a9424df · outbound

This paper cites an unresolved cited work.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Unresolved cited work

Reference 38

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source=pdf_text observed=2026-08-03T21:51:15.534468Z digest=sha256:8478a0d8693d237fc602838c52964060dbfc5246872d9a56ab1e44f12e765d08

Observation 94da1fe3-10bc-4e45-a5b4-d03b9f8f1337 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Gemini: A Family of Highly Capable Multimodal Models

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source=pdf_text observed=2026-08-03T21:51:15.538461Z digest=sha256:98d8ab56d39eb67da40246e8f07e777d242a04965dad248d53c0da2b7c7280c4

Observation a5fc7089-9bb0-4ad6-b828-18c295c3b13d · outbound

This paper cites Qwen2.5-vl, 2025.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Qwen2.5-vl, 2025

Reference 40

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source=pdf_text observed=2026-08-03T21:51:15.542422Z digest=sha256:29a01f14143da4e2ebafddc34bbe5dd137c109483011e71a8c6ec661065c4957

Observation 00cfe021-7c9d-4ee7-b4e3-5d6b13817609 · outbound

This paper cites Qwen3, 2025.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Qwen3, 2025

Reference 41

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source=pdf_text observed=2026-08-03T21:51:15.546597Z digest=sha256:9c3c66c05e0525aebbe4d912553feafb6c4e2208828ee3cc3438d3e6566f8d0e

Observation 61773baf-45a3-4e0a-af89-72c3c0a2723a · outbound

This paper cites an unresolved cited work.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Unresolved cited work

Reference 42

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source=pdf_text observed=2026-08-03T21:51:15.550514Z digest=sha256:7e8194314afac9e2a54a7b996b96037e3001afe771dd8a5cc652dd7e7e45b13c

Observation 2b90cb22-601c-4f1b-af40-15fce5df6594 · outbound

This paper cites Only: One-layer intervention suf- ficiently mitigates hallucinations in large vision-language models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Only: One-layer intervention suf- ficiently mitigates hallucinations in large vision-language models

Reference 43

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source=pdf_text observed=2026-08-03T21:51:15.554331Z digest=sha256:80d43a07a49af7084dd7fa64cd00ba16b724fb1f37ae3503f745aeb1d0f8e712

Observation 7901e68e-1256-4f6f-8687-125f3d63a3c0 · outbound

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

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Reference 44

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source=pdf_text observed=2026-08-03T21:51:15.558216Z digest=sha256:8e86c0f4e522b3da63d9b006fe06aa5568235f49a423eeea2012d04681d32cf9

Observation 6b207688-88b0-4d5c-aed8-a7c1ea1c2d7d · outbound

This paper cites The generative ai para- dox:” what it can create, it may not understand”.Int.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task The generative ai para- dox:” what it can create, it may not understand”.Int

Reference 45

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source=pdf_text observed=2026-08-03T21:51:15.562192Z digest=sha256:3aa9a10b84ef711a0c36931587b9073360b31c63e29da48026e58dfa1022a38d

Observation a111ca3d-432d-437e-98f0-102c1a49bfa8 · outbound

This paper cites Generate, but verify: Reducing hallucination in vision-language models with ret- rospective resampling.Adv.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Generate, but verify: Reducing hallucination in vision-language models with ret- rospective resampling.Adv

Reference 46

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source=pdf_text observed=2026-08-03T21:51:15.565869Z digest=sha256:ea9e51a2c65a6738911bbeed2edcc23f83a4b968f4dfeb90db28e84ca9f640cc

Observation 5f0c4592-3a93-47f9-8306-fc744549ecae · outbound

This paper cites Nullu: Mitigating object hallucinations in large vision-language models via halluspace projection.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Nullu: Mitigating object hallucinations in large vision-language models via halluspace projection

Reference 47

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source=pdf_text observed=2026-08-03T21:51:15.569565Z digest=sha256:1778535e3dabb73b2c06fb1b36f787b85a2af423c8a34a6e22423d8ca89f4133

Observation 509e89d4-44a3-45bc-838e-9554f6dca3bf · outbound

This paper cites Mitigating hallucinations in large vision- language models via dpo: On-policy data hold the key.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Mitigating hallucinations in large vision- language models via dpo: On-policy data hold the key

Reference 48

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source=pdf_text observed=2026-08-03T21:51:15.573424Z digest=sha256:19727b86d6b4d4d5283780c3762bd05b44588a240d6f997d0fd137a0904ca5ae

Observation 731ca74e-c404-492b-ba92-704f4d8cc9a1 · outbound

This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 49

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source=pdf_text observed=2026-08-03T21:51:15.577326Z digest=sha256:bf9080047c312820e60e4d20d5c584412fb59653968fdabb8ab43e28e5682754

Observation 2f70ae0f-849a-463f-922d-1fc7e308dde9 · outbound

This paper cites Clearsight: Vi- sual signal enhancement for object hallucination mitigation in multimodal large language models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Clearsight: Vi- sual signal enhancement for object hallucination mitigation in multimodal large language models

Reference 50

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source=pdf_text observed=2026-08-03T21:51:15.581251Z digest=sha256:d06d6f1f10290b94dbe560c0afa03a53f44b0c692d69956fceb2aed15bf2df05

Observation 785d7eff-dd39-4eb0-a7f8-d6490004191a · outbound

This paper cites Mitigating object hallucination in large vision-language models via image-grounded guidance.Int.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Mitigating object hallucination in large vision-language models via image-grounded guidance.Int

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source=pdf_text observed=2026-08-03T21:51:15.585110Z digest=sha256:e0f27b425d5526d4d8c46157b3e71a771ee064c203ffc4c8f76c4d18043fd4bc

Observation d3fa2bf7-fa44-43cc-9bf6-65c648b098a1 · outbound

This paper cites Why lvlms are more prone to hallucinations in longer responses: The role of context.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task Why lvlms are more prone to hallucinations in longer responses: The role of context

Reference 52

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source=pdf_text observed=2026-08-03T21:51:15.589085Z digest=sha256:f88855a8f163049929da564addb130eb9ce42d9d27bdebdd1584ebe1be2bb59d

Observation 114a8911-108e-4726-82d0-b40bb1f7a7d7 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 53

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source=pdf_text observed=2026-08-03T21:51:15.592797Z digest=sha256:7e2b591747317824451351055c26bc76903f9daa92ea4da0c381ee4a32c68025

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