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Paper Citation Record · LEDGER

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models

As of 20 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 0 inbound Pith citation observations for arXiv:2505.01958.

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

pith.paper-citation-record.v1
2505.01958 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:09:10.131920Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

65 of 65 outbound references displayed

  • verified exact2
  • verified fuzzy6
  • unresolved57
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2ff14514-ab87-4c75-9ef7-80dfe6a0ba95 · outbound

This paper cites URL: " 'urlintro :=.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models URL: " 'urlintro :=

Reference 1

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Observation 291047fe-20df-45da-9481-1e10837ae355 · outbound

This paper cites write newline.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models write newline

Reference 2

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Observation e47e5a0f-27d9-4802-85f0-dbbfb6373578 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 3

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Observation 64e3e9f0-cec5-4c58-88ab-1233756eb357 · outbound

This paper cites Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention

Reference 4

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Observation bc829461-4636-4867-817d-817364584e19 · outbound

This paper cites Lawrence Zitnick, and Devi Parikh.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Lawrence Zitnick, and Devi Parikh

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 26b133c6-9dcf-4fb7-b327-7c68559fd0d0 · outbound

This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 6

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Observation 169d7ed1-330c-4cf0-aa64-ae1888ec9586 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models On the Opportunities and Risks of Foundation Models

Reference 7

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Observation b444f118-a0b6-4790-81b1-a377158263cb · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 8

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Observation 13cd9fef-8267-47e8-8b3a-38d5b39c3483 · outbound

This paper cites Language Models are Few-Shot Learners.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Language Models are Few-Shot Learners

Reference 9

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source=arxiv_source observed=2026-08-16T04:09:09.800524Z digest=sha256:75efa7bfdca3d8b7e22ca38c7355bb74b4ed59307e4b1ea3e03f7563b26ea489

Observation f155b18f-1865-4dbe-b895-53d94d7c8249 · outbound

This paper cites A Unified Hallucination Mitigation Framework for Large Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models A Unified Hallucination Mitigation Framework for Large Vision-Language Models

Reference 10

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Observation 315a337f-2e38-4833-b56f-ecfbdfcc351a · outbound

This paper cites ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

Reference 11

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Observation ea63711a-4442-471c-a380-032f2f98ac1b · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-16T04:09:09.817526Z digest=sha256:68bf97d4c7b48acd91ce20cb537e50a88bd327515a36d211f7c0021f9b6a2a11

Observation fef02ba7-8bcb-4790-80a0-60f6f5e98340 · outbound

This paper cites HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding

Reference 13

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Observation c90abbcd-be6b-4ae0-9dfd-0863a1726ba5 · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Gonzalez, Ion Stoica, and Eric P

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 16ef4bfa-cbe1-4900-87de-38c1c892ea95 · outbound

This paper cites Glass, and Pengcheng He.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Glass, and Pengcheng He

Reference 15

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:09.833222Z digest=sha256:bacaa7333709973249b466053bc533b0224545586189b7c3b616d1352821ae2d

Observation 4c2399b1-84f0-4864-bac2-bc55290b8bb5 · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 16

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source=arxiv_source observed=2026-08-16T04:09:09.838358Z digest=sha256:36c1da20b5eb84717f59dc97eb244a9d403e1d4cb135247485f23cf63dc1e601

Observation c5db75cd-5142-4330-8ce4-f5067ae79c78 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 17

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Observation 74a391d2-4124-4d86-9640-2f593caf75a7 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 18

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Observation 52821102-ff58-4ae6-b65e-8a46408b3547 · outbound

This paper cites MultiModal-GPT: A Vision and Language Model for Dialogue with Humans.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models MultiModal-GPT: A Vision and Language Model for Dialogue with Humans

Reference 19

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source=arxiv_source observed=2026-08-16T04:09:09.854957Z digest=sha256:c51b2d9adaaa2544215106cc24a086ff9e43feec2af14be28427f11fd3b5199d

Observation 6ca189dd-5b22-4e12-9bec-39f7b804aa5b · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Detecting and Preventing Hallucinations in Large Vision Language Models

Reference 20

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Observation 960b740f-12ee-421e-b0ce-789845138e83 · outbound

This paper cites Conditional probing: measuring usable information beyond a baseline.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Conditional probing: measuring usable information beyond a baseline

Reference 21

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Observation 9241c9f9-3c94-4407-8a15-720e6e79d31b · outbound

This paper cites OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation

Reference 22

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Observation af01d3cb-0b80-457b-8101-c5b93f5fcbf2 · outbound

This paper cites OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation

Reference 23

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source=arxiv_source observed=2026-08-16T04:09:09.878598Z digest=sha256:68c5346a168966d00fc94d445abbbfce3fab0173debe91e6edd760a42b252493

Observation e2d55118-93a7-4eff-ab3e-8831eb90cd91 · outbound

This paper cites Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate

Reference 24

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Observation a2bccc70-0215-436e-ba94-2fb10bbfb9e5 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 25

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source=arxiv_source observed=2026-08-16T04:09:09.889729Z digest=sha256:500f48a376b95d82335e38e004a3abc3e7d8999e07aa94f3b8d863fe1e9966f1

Observation 7281ff7e-b2e9-47d7-88ae-5c1bd9b5eac1 · outbound

This paper cites FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback

Reference 26

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source=arxiv_source observed=2026-08-16T04:09:09.896689Z digest=sha256:8cd09be83d0a3eaaf0fe9973f712e142765c65e74e69f4bf7fc8192a9c8805ec

Observation fd1d568b-2ed1-4199-8241-9c91a0f9903c · outbound

This paper cites FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models

Reference 27

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Observation ef51ecc8-3a77-4b15-a576-d3e5f10fd105 · outbound

This paper cites Shamma, Michael S.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Shamma, Michael S

Reference 28

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Observation 3ace4613-6887-4700-a131-f69c8f7403e8 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 29

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source=arxiv_source observed=2026-08-16T04:09:09.913113Z digest=sha256:cdf0ae6cda96a231e8a45e5e8556d6340101621f447e3a2202775638c19b243c

Observation 66c6dc39-9c9e-4c04-8e42-40df7618a967 · outbound

This paper cites http://www.cs.toronto.edu/ kriz/cifar.html Cifar-100 (canadian institute for advanced research).

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models http://www.cs.toronto.edu/ kriz/cifar.html Cifar-100 (canadian institute for advanced research)

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-16T04:09:11.630644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:09.918524Z digest=sha256:a5bfc0966453be1241324a799396364ed2d077400d7ef15063616a833351318f

Observation 939944ff-f12c-4a82-af25-3a4dc4163569 · outbound

This paper cites Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding

Reference 31

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source=arxiv_source observed=2026-08-16T04:09:09.923794Z digest=sha256:af301accf55ab21165e41d23ffa7252d00c78d73e9fb8e8cefcd0b637bfe8006

Observation 3dfcf927-d3a7-4e88-9dc0-ae2167507f64 · outbound

This paper cites Otter: A Multi-Modal Model with In-Context Instruction Tuning.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Otter: A Multi-Modal Model with In-Context Instruction Tuning

Reference 32

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Observation 0d5ac2f8-c172-44d9-ab0f-9665a35e2e7e · outbound

This paper cites Vi \' e gas, Hanspeter Pfister, and Martin Wattenberg.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Vi \' e gas, Hanspeter Pfister, and Martin Wattenberg

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:09:11.612974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:09.934151Z digest=sha256:daf8c43e3372a058ce6f8cb3a52295c894eb919bc63253137fb2aff0ebae9526

Observation 4e4e2149-cd72-4138-8832-049ec20fc7f8 · outbound

This paper cites Silkie: Preference Distillation for Large Visual Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Silkie: Preference Distillation for Large Visual Language Models

Reference 34

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source=arxiv_source observed=2026-08-16T04:09:09.938714Z digest=sha256:e187cc466f5c88b16b8fab6bfc45f4008abdc0149e278242cbf2f461cffec90c

Observation e2270429-29af-40b3-9791-bcce5754e625 · outbound

This paper cites M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning

Reference 35

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source=arxiv_source observed=2026-08-16T04:09:09.944879Z digest=sha256:e25f0d8f3d7920f24b7b32cd55065fa17460bb7bd11be9f4bfba0572e5669906

Observation 3a66e588-8be1-4632-956a-0d226799e1d7 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 36

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 66aff8fe-f596-4b30-807b-c2997b756f18 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 37

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Observation 4d03a78d-6cc8-40c6-9516-e0cd02174392 · outbound

This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll \' a r, and C.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll \' a r, and C

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:09:11.591750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:09.960543Z digest=sha256:06f7ccaf4bb14f6a61d71475924e0a6347c80e92bbdae869772cafab5f06caed

Observation f7f035ac-0db7-4611-b67b-3780234575f9 · outbound

This paper cites HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:09.965781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:09.965781Z digest=sha256:25a48a528c1b6d5e212c1750ae5db7f672a3fcccd9feb26a35187c0be98dcd8d

Observation 93d3bef7-b16a-4af0-8d04-15d8c89ea91a · outbound

This paper cites Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:09.983307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:09.983307Z digest=sha256:6261b9afe5536254cb14c9f5d236697aaffc9b255535b1403c82626b49cfe6c2

Observation 9d996f38-a577-49d2-a9ae-b44d04fa810b · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Improved Baselines with Visual Instruction Tuning

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:09.989194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:09.989194Z digest=sha256:a901bf4fa2250706f06c3b3f039bb3d54acb33c42f2f7f3eb0703310e57a9ce0

Observation 9307ede5-8145-4d8d-a6b3-be901d812704 · outbound

This paper cites Visual Instruction Tuning.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Visual Instruction Tuning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:09.994695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:09.994695Z digest=sha256:c423d719f9b0e8d29a98e703e96201f030b643f2689d9b956abe0d1e9e74162f

Observation aa59536c-c0f7-4338-b3b8-289722cb3ccd · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:09:11.572882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:09.999830Z digest=sha256:62fb74d278c15b8bea5511475e3bc0242cb24288635c5a6ff1b0d5e35508270a

Observation 69281292-d9cd-4457-ac01-44b3b09e1696 · outbound

This paper cites Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.005267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.005267Z digest=sha256:ada5683d8e653c38bc3582431a3acb2b51765673baa82940ef4c3b6ad0e4c1b4

Observation 75bf3abe-ae22-4794-a08e-2e6f44e881f1 · outbound

This paper cites Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.011649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.011649Z digest=sha256:1e25460ea7545451fd18ae7f682bbd6e719cbe768bbbdfbb61ef710be4ae417a

Observation f543424a-158f-41b7-9e83-17b461da4e78 · outbound

This paper cites FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.017224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.017224Z digest=sha256:b243fdfdf191383d90735fc1a12df54b85f396564e8a71e896d0a1e98359fddc

Observation 3d0c9b9e-3c07-452c-a3d8-44d36af75db4 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:09:11.551956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:10.022048Z digest=sha256:a917cfe4f2bfa963859f1f9230bfc24698c2102c888efa2eddbc9200f046bb36

Observation b762cd56-8aa0-4234-99da-cb75d1ff5ce2 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:09:11.533805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:10.027043Z digest=sha256:8b271261daa3979d41da226145f8f28e73ec4f16ef41037fd8489cf5358ebf78

Observation 34e874ac-1d7c-4cda-9bb6-76587af74ea4 · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.031955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.031955Z digest=sha256:6b82fc82b1a8ffd0e718f2c6308664bd57693da517114da1e58a7d32223b86f3

Observation 0d9d5b07-a867-4316-a517-c9e96dfb4d4f · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.038010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.038010Z digest=sha256:2dd19e9ad47a8a07a0fdc310e6838098f0acf9129325fb411e8c172f36d5253c

Observation 747b0b46-4817-48e1-994c-1d6498bf21aa · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.043263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.043263Z digest=sha256:d0583b98a0f2cd7b9b80083f1fbc00282e3bbb97d736399d0beaac0ec3888542

Observation 11f11ee6-4e6f-4ed3-b254-0f2c8f1635b1 · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.048586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.048586Z digest=sha256:5dca46ead2a34c65f509eb5628ba8b9eb0059ca3609949209c046b6c6a10c0af

Observation 142f1c70-7db9-4233-aa11-ab4a8414bf81 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.056392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.056392Z digest=sha256:abd8b0142963a50c2ab2e709cd01b529d657ec41be7affea899f170cb6df69c4

Observation 7868013d-3d7b-4816-a93d-33f54325c4f8 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.061904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.061904Z digest=sha256:ad17883434629186ec41383fbb61f91c54e9bcbe2fc7c5f3ae7cee4bcbdb4f6f

Observation 0cebcbfb-05fd-4b4b-955f-aa74e573046a · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:09:11.513393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:10.066874Z digest=sha256:12567fa5dc7f87f50c727ff5a0399477b8344845d95c0230cd039bc023cae9db

Observation cc882543-8876-47ce-9805-ae6d2841b6a3 · outbound

This paper cites mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.072438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.072438Z digest=sha256:a94fae4576fc719d87b06bb8f48a4619d73224c81c5aacbb357a864fdcb912bb

Observation 6c46b117-0a74-440e-b7a5-07b83db912b2 · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Woodpecker: Hallucination Correction for Multimodal Large Language Models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.077725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.077725Z digest=sha256:9ab21779b1de822775c3911920ce856e25670a87512faf3465609003dbd1cb6e

Observation 127af464-70a5-427e-9594-e69301748643 · outbound

This paper cites RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.083521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.083521Z digest=sha256:11bcb49ecdde43eb0f4ee4ebd386dc8a052c9b64e8dff0d62df2fb5debb90e57

Observation 054cc23b-d37f-4f1d-8c80-ec093c9f8650 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.090321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.090321Z digest=sha256:481857d5e0ff8598acbbbd38148b5b1154f23ab389279bd77eb24897914e16ca

Observation ea64fb64-530e-4b23-87fe-71c4c546bfeb · outbound

This paper cites Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.095596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.095596Z digest=sha256:0a4e8aef4b2ca92a4bfbcf086435d45fa51d1c6d3241137e744072f1db9a82f9

Observation 6b677fcf-5037-466f-b9e6-6d9f5236316f · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 63

Resolution
verified exact
doi, observed 2026-08-16T04:09:10.224568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-16T04:09:10.102131Z digest=sha256:5c929d4b552ed09a8323947d5867bf8491f5aaa7613d8e1ca9438d28976f2495

Observation 6937adbf-9929-491b-83af-f91e8df53be0 · outbound

This paper cites an unresolved cited work.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Unresolved cited work

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.109363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.109363Z digest=sha256:e65a80b94d3fd8ef47a659bc1af86993c037365b37ad80bfc8b8f9b61f3fa4be

Observation 096fe528-5219-4053-a4d1-79336491f6e3 · outbound

This paper cites Aligning Modalities in Vision Large Language Models via Preference Fine-tuning.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.116502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.116502Z digest=sha256:79544d606a807f0c1a87c55c7a84ff3ff36b404ccf9e3a3b71f263b87e8795bf

Observation e1a5ef50-d9b6-4161-b142-4ad3dbadc070 · outbound

This paper cites Analyzing and Mitigating Object Hallucination in Large Vision-Language Models.

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models Analyzing and Mitigating Object Hallucination in Large Vision-Language Models

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.123595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.123595Z digest=sha256:d587c9313009d0bb9975ecbd57b0428971cf900fdd1ce4c7a25c735bb9da1fed

Observation 1f9073d7-8db3-4994-b6b1-91378e4daf84 · outbound

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

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-16T04:09:10.131920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:09:10.131920Z digest=sha256:6845e027acff923c901fa85b867a89d91849fc5d9843baba0b8afb7773850ec8

Pith citing papers

No inbound Pith citation observations are available.