Paper Citation Record · LEDGER

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2505.07001.

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

pith.paper-citation-record.v1
2505.07001 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:31:52.523995Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T12:37:57.709258Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T12:44:39.385265Z

Reference resolution

52 of 52 outbound references displayed

verified exact2
verified fuzzy22
unresolved27
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9cc42cae-a13b-44c4-bb7f-767f048488fb · outbound

This paper cites GPT-4 Technical Report.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models GPT-4 Technical Report

Reference 1

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Observation 82f8004f-f120-4dde-bb38-c9a22c1f4c14 · outbound

This paper cites Gas- troenterology 159(1), 335–349 (2020) 10 Khanal, Pokhrel, Bhandari et al.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Gas- troenterology 159(1), 335–349 (2020) 10 Khanal, Pokhrel, Bhandari et al

Reference 2

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Observation ead922fb-a727-4f04-ab71-574aef3d6b57 · outbound

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

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Hallucination of Multimodal Large Language Models: A Survey

Reference 3

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Source-reported events for the cited work

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Observation 5ef7959a-9dd7-427d-8598-ac7224d1c332 · outbound

This paper cites In: Proceedings of the ACL work- shop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Proceedings of the ACL work- shop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization

Reference 4

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Observation 2ebcf697-b6b8-4406-8d59-9c30fa3641e9 · outbound

This paper cites Sci- entific data 7(1), 283 (2020).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Sci- entific data 7(1), 283 (2020)

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee1a18f5-eba2-43e3-807a-d7763fd6c350 · outbound

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

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.336178Z

Source-reported events for the cited work

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Observation f44972b5-f9d9-46db-942b-e555d24464de · outbound

This paper cites In: Bebis, G., Yin, Z., Kim, E., Bender, J., Subr, K., Kwon, B.C., Zhao, J., Kalkofen, D., Baciu, G.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Bebis, G., Yin, Z., Kim, E., Bender, J., Subr, K., Kwon, B.C., Zhao, J., Kalkofen, D., Baciu, G

Reference 7

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Observation ec6d48ba-186d-4ac2-a926-8f4dc309f0f5 · outbound

This paper cites DeepSeek-V3 Technical Report.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models DeepSeek-V3 Technical Report

Reference 8

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Source-reported events for the cited work

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Observation ff53cb07-3c2e-4be0-a45f-f50c2ac1bb0f · outbound

This paper cites Gastric Cancer26(2), 275–285 (Mar 2023).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Gastric Cancer26(2), 275–285 (Mar 2023)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.239836Z

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Observation c043a6e5-e490-403d-a7bb-f26227b31fef · outbound

This paper cites Nature630(8017), 625–630 (2024).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Nature630(8017), 625–630 (2024)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.352305Z

Source-reported events for the cited work

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Observation 28530435-8ab1-4476-8f7d-9b898bc9e313 · outbound

This paper cites In: Proceed- ings of the First International Workshop on Vision-Language Models for Biomedi- cal Applications.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Proceed- ings of the First International Workshop on Vision-Language Models for Biomedi- cal Applications

Reference 11

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Source-reported events for the cited work

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Observation 35dc5f7c-5de5-4554-be1b-cffe434d60b3 · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence (2024).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Proceedings of the AAAI Conference on Artificial Intelligence (2024)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.217493Z

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Observation 9013aadd-9265-4b4f-9590-ae91c56696ff · outbound

This paper cites In: Conference and Labs of the Evaluation Forum (2023).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Conference and Labs of the Evaluation Forum (2023)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.204187Z

Source-reported events for the cited work

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Observation e17b08e6-fc89-4ca0-991a-255372c299ff · outbound

This paper cites ICLR1(2), 3 (2022).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models ICLR1(2), 3 (2022)

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 582f414c-5131-452e-9b0c-eebb35e655b4 · outbound

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

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.372530Z

Source-reported events for the cited work

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Observation f14490c4-2087-4b81-86d8-1b5f5df02fbc · outbound

This paper cites Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:31:52.745218Z

Source-reported events for the cited work

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Observation 8621549c-5adc-4a12-8d59-f5535813603a · outbound

This paper cites In: Hallucination-Aware Multimodal Benchmark for GI Analysis 11 Workshop on Machine Learning for Multimodal Healthcare Data.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Hallucination-Aware Multimodal Benchmark for GI Analysis 11 Workshop on Machine Learning for Multimodal Healthcare Data

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.180925Z

Source-reported events for the cited work

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Observation 69826e25-4e11-45a0-8f10-abc6d41ee275 · outbound

This paper cites CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generation.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generation

Reference 18

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Source-reported events for the cited work

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Observation 026ca8ec-ccde-4fa2-93b8-ab54718bd027 · outbound

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

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models

Reference 19

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Observation f10ff1ec-bf7c-4754-944b-b4fffb9406a9 · outbound

This paper cites Diagnostic and interventional imaging (2024).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Diagnostic and interventional imaging (2024)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.167431Z

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Observation db9745f2-70b1-4982-a6c2-4dcbcffbea85 · outbound

This paper cites EClinicalMedicine53 (2022).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models EClinicalMedicine53 (2022)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.154052Z

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Observation 133e5c87-ca3d-4343-9039-8338842ea08d · outbound

This paper cites an unresolved cited work.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:31:53.140897Z

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Observation 3c08dc73-a96b-4fb6-b12e-7050c791cf9c · outbound

This paper cites In: Text summarization branches out.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Text summarization branches out

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.127337Z

Source-reported events for the cited work

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Observation 11cbd8c2-b350-45e3-bc7c-19e3b172f106 · outbound

This paper cites In: Computer vision– ECCV 2014: 13th European conference, zurich, Switzerland, September 6-12, 2014, proceedings, part v 13.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Computer vision– ECCV 2014: 13th European conference, zurich, Switzerland, September 6-12, 2014, proceedings, part v 13

Reference 24

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Source-reported events for the cited work

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Observation 0a9c98e4-74e1-4c32-b853-0768c08774d0 · outbound

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

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.417823Z

Source-reported events for the cited work

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Observation c3c13ec4-220f-457d-bbe1-eae6afe98c79 · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Improved Baselines with Visual Instruction Tuning

Reference 27

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Observation 9d8d076d-7891-4fc8-bb78-783f4d66dd12 · outbound

This paper cites Advances in neural information processing systems36, 34892–34916 (2023).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Advances in neural information processing systems36, 34892–34916 (2023)

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.425914Z

Source-reported events for the cited work

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Observation c9daddba-9102-4426-8f19-b87d8415f7ee · outbound

This paper cites Frontline Gastroenterology 14(4), 306–311 (2023).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Frontline Gastroenterology 14(4), 306–311 (2023)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.096533Z

Source-reported events for the cited work

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Observation 0eac8e70-4fa0-4b2a-b593-45ecb0e0c307 · outbound

This paper cites GE- Portuguese Journal of Gastroenterology24(6), 269–274 (2017).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models GE- Portuguese Journal of Gastroenterology24(6), 269–274 (2017)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.083382Z

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Observation c790a9f7-3a36-4506-910b-3f35ba979964 · outbound

This paper cites Cogent Engineering9(1), 2084878 (2022).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Cogent Engineering9(1), 2084878 (2022)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.070301Z

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Observation 09088d94-10f2-47f4-9ae6-d1a5be9cd95c · outbound

This paper cites Annual review of psychology68(1), 465–489 (2017).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Annual review of psychology68(1), 465–489 (2017)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.056764Z

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Observation eca6fa88-7482-4c63-b552-3f99bf226312 · outbound

This paper cites In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.043253Z

Source-reported events for the cited work

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Observation e72d4caa-38a1-4ee4-981d-26376b4f8eef · outbound

This paper cites In: Proceedings of the 8th ACM on Multimedia Systems Conference.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: Proceedings of the 8th ACM on Multimedia Systems Conference

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.449964Z

Source-reported events for the cited work

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Observation 60e44ef9-f086-4553-ae56-6e7751cf0692 · outbound

This paper cites NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal Vision.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal Vision

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.453902Z

Source-reported events for the cited work

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Observation f038d8cd-cf86-4498-ad8d-d9076ac3140b · outbound

This paper cites TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:31:52.658484Z

Source-reported events for the cited work

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

Observation fa22a29c-b4e4-4400-a583-77d5c8721ecb · outbound

This paper cites Artificial Intelligence in Medicine 143, 102606 (2023).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Artificial Intelligence in Medicine 143, 102606 (2023)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.021111Z

Source-reported events for the cited work

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

Observation ea3eb8ef-e6ad-436f-9480-67619efd9e02 · outbound

This paper cites Object Hallucination in Image Captioning.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Object Hallucination in Image Captioning

Reference 38

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Source-reported events for the cited work

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Observation c70764e2-b587-47bc-bff1-708206248894 · outbound

This paper cites Scientific Reports 13(1), 4171 (2023).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Scientific Reports 13(1), 4171 (2023)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:53.007880Z

Source-reported events for the cited work

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Observation 93e4bf31-e852-4cb6-af19-5732ef6cb7bc · outbound

This paper cites In: 2022 IEEE 19th India Council Interna- tional Conference (INDICON).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models In: 2022 IEEE 19th India Council Interna- tional Conference (INDICON)

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:52.994626Z

Source-reported events for the cited work

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

Observation 2f83b2ae-a4d1-4451-9774-bafc5f0b2e83 · outbound

This paper cites Scientific Reports14(1), 9330 (2024).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Scientific Reports14(1), 9330 (2024)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:52.981740Z

Source-reported events for the cited work

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Observation 0da5ed70-334c-43b7-aa76-35f61609a17b · outbound

This paper cites Medical Vision Language Pretraining: A survey.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Medical Vision Language Pretraining: A survey

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.479566Z

Source-reported events for the cited work

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Observation b3668b4b-ca81-478d-ae69-d4882e00d84f · outbound

This paper cites Nature Medicine pp.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Nature Medicine pp

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:52.968623Z

Source-reported events for the cited work

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Observation 0aebdc4d-8c04-4afd-8e76-16e84094b847 · outbound

This paper cites Diagnostics13(4) (2023).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Diagnostics13(4) (2023)

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:52.954242Z

Source-reported events for the cited work

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

Observation 7485744c-0ec6-4ded-843b-54d8214e5161 · outbound

This paper cites Scientific Data8(1), 142 (May 2021).

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Scientific Data8(1), 142 (May 2021)

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:52.942047Z

Source-reported events for the cited work

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

Observation f6264476-cf02-46ff-b5ce-750a6b1d955e · outbound

This paper cites an unresolved cited work.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:31:52.929580Z

Source-reported events for the cited work

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Observation 3df70971-0aa6-49cd-aa92-32c58cd35a64 · outbound

This paper cites Mitigating Fine-Grained Hallucination by Fine-Tuning Large Vision-Language Models with Caption Rewrites.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Mitigating Fine-Grained Hallucination by Fine-Tuning Large Vision-Language Models with Caption Rewrites

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.498670Z

Source-reported events for the cited work

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Observation d5545266-5a59-4674-a256-3b620863620b · outbound

This paper cites an unresolved cited work.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:31:52.917348Z

Source-reported events for the cited work

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Observation a530b638-e217-474b-b78f-27299fee2a5d · outbound

This paper cites Qwen2 Technical Report.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Qwen2 Technical Report

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.506943Z

Source-reported events for the cited work

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Observation c036420e-65c5-42e5-904c-a89d68cd9053 · outbound

This paper cites mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.511269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4891a39-c745-4e51-8d00-c8c9aafdc54b · outbound

This paper cites HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.515471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e235796-87d5-4eb7-bf34-037e04bb9c8c · outbound

This paper cites Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:52.519576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df3aea9a-51b4-4961-bf7e-a8da7b194d62 · outbound

This paper cites an unresolved cited work.

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:31:52.904518Z

Source-reported events for the cited work

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

Pith citing papers

Observation 7fc5905c-c717-48fd-a88b-dc890f11d98b · inbound

Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering cites this paper.

Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:44:39.386833Z

Source-reported events for the cited work

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