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Paper Citation Record · LEDGER

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding

As of 14 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 4 inbound Pith citation observations for arXiv:2502.01056.

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

pith.paper-citation-record.v1
2502.01056 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:50:15.232756Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T00:32:49.666202Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T00:35:10.140293Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 42781bfb-29b6-459d-9c07-cef97fc9ffb5 · outbound

This paper cites write newline.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding write newline

Reference 1

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no resolver link, observed 2026-08-09T16:50:15.082640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.082640Z digest=sha256:c8662433f63b486ecd1df39dacf5f9521d5fa467b7e297159e685378417ffe00

Observation 14194176-1e37-42be-b061-6cebef72a78c · outbound

This paper cites GPT-4 Technical Report.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding GPT-4 Technical Report

Reference 2

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no resolver link, observed 2026-08-09T16:50:15.093483Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-09T16:50:15.093483Z digest=sha256:c65ecf39c291e3ca727fb91e65d7470aef11b8dadc2ebb8133c52edd582c39aa

Observation 31ee6b78-5bf8-4c6a-af2d-5a85af01fca0 · outbound

This paper cites Self-rag: Self-reflective retrieval augmented generation.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Self-rag: Self-reflective retrieval augmented generation

Reference 3

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raw_fallback, observed 2026-08-09T16:50:15.691252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.097016Z digest=sha256:e7968cdb5aa8bc66648485a7f18a9f23a5667e386e46eeb935e6f1b9ad527182

Observation e9ba749c-bd2e-4326-9567-6c1a68ca8e0f · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 4

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no resolver link, observed 2026-08-09T16:50:15.099772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.099772Z digest=sha256:6d15ebac962e6edc2d351a95edab3fec3b13072b90f111b6568553fd72a63b71

Observation 100da0c5-6852-4cae-bf47-81d0218cce9b · outbound

This paper cites F., G \'o mez, L., and Karatzas, D.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding F., G \'o mez, L., and Karatzas, D

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.683460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.102517Z digest=sha256:844e4a9792fd750385a818f423d38e031569c2ea734cfd7a16051ca09ef6ac53

Observation 55e95045-643c-4a77-9db2-8d9d92c42616 · outbound

This paper cites In-context sharpness as alerts: An inner representation perspective for hallucination mitigation.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding In-context sharpness as alerts: An inner representation perspective for hallucination mitigation

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.675917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.106134Z digest=sha256:738963af421c87228a43164c4e7d56075ae7306bfc6b9ca9b330f758a1d987bf

Observation cc6cd000-f8d2-49bc-b1ee-4c10b078d145 · outbound

This paper cites In-context sharpness as alerts: An inner representation perspective for hallucination mitigation.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding In-context sharpness as alerts: An inner representation perspective for hallucination mitigation

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.667710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.109531Z digest=sha256:fafebb3935221fcf39296f5e55cc1d2f146065db36e03bf10aae8ff2c3128293

Observation 7579b3c8-d13b-42cb-9f58-f41c5eec65f7 · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Halc: Object hallucination reduction via adaptive focal-contrast decoding

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.659152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.112636Z digest=sha256:64c11d9f80ead887c141d7b7de2d921af1a68f28e21c1936fc8a1323c53514f3

Observation 35d4fbbc-ac4a-42c4-bb7d-01c76904979f · outbound

This paper cites E., et al.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding E., et al

Reference 9

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no resolver link, observed 2026-08-09T16:50:15.115868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.115868Z digest=sha256:709d8d6bce09e27e3a233c47b3d71a45bf8563e45f1a529d026a372ef0d83311

Observation 9b1d5a21-5df9-4456-8f4c-559d0662dcf7 · outbound

This paper cites Chain-of-verification reduces hallucination in large language models.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Chain-of-verification reduces hallucination in large language models

Reference 10

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.118585Z digest=sha256:d32140b238e5173acd1765948e0b80d64672eecc377f1d507a036b27c0368dd9

Observation 0d2b5eed-37ff-4cb3-9568-0301ac622ee8 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding An image is worth 16x16 words: Transformers for image recognition at scale

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.121327Z digest=sha256:5b5e862fc3c648f36990954144a81da5364a52cd679cd031e1dff2e5171c579b

Observation 2c1938d6-2de2-45ec-8b39-3a10e69d616c · outbound

This paper cites an unresolved cited work.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Unresolved cited work

Reference 12

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raw_fallback, observed 2026-08-09T16:50:15.641195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.123774Z digest=sha256:a993c44e3762542c66f9e0c59aebd329a195139103df6fc2c29b08f00e7fd3e3

Observation da2857a1-21b6-4116-aa45-fbf3c6238fb8 · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 13

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no resolver link, observed 2026-08-09T16:50:15.126150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.126150Z digest=sha256:f16c8caade21d03805a92c8d54928daaa2ce5a43fa85b8cd16ab0bd1e62c9acd

Observation a856a4f8-0921-48fe-baa7-c8e0a00b71c0 · outbound

This paper cites A., and Gal, Y.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding A., and Gal, Y

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.631401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.128833Z digest=sha256:f026dcc3c57a3a065a385ce78ec8b138d7f8f6541a435ff2c6fa1a73b97391b5

Observation f77f3bf4-f1a4-4aad-80dd-1aea5e335433 · outbound

This paper cites Knowledge-centric hallucination detection.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Knowledge-centric hallucination detection

Reference 15

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no resolver link, observed 2026-08-09T16:50:15.131314Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.131314Z digest=sha256:ec342882840ed7c50775f62b4f04fb3baa11089277c9c10ff56b3733d0dc3ad3

Observation f1ba08b0-0032-4942-a8a9-6751b4b74687 · outbound

This paper cites J., Madotto, A., and Fung, P.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding J., Madotto, A., and Fung, P

Reference 16

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unresolved
no resolver link, observed 2026-08-09T16:50:15.133617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.133617Z digest=sha256:fb7d067e2562aab4c19b998991feaf26662a529a870900c8a279604a440beb84

Observation 1ef5f3d7-3a45-40ba-82fb-0feb97a4127c · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Mitigating object hallucinations in large vision-language models through visual contrastive decoding

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.136463Z digest=sha256:b210678e25334f3908300aa56557cc763cc43a0c51d88bba5d521353a84751cd

Observation 9e86b6e7-f207-49aa-a554-bbcbed211fc0 · outbound

This paper cites an unresolved cited work.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Unresolved cited work

Reference 18

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verified exact
doi, observed 2026-08-09T16:50:15.286794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6cfe7678-13cb-4b1f-81a8-1dc2ba4b6012 · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 19

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no resolver link, observed 2026-08-09T16:50:15.142173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.142173Z digest=sha256:5a125983f1058df57719fd136aadbc5efa728201324121e1d03064134d518521

Observation 1370e302-a6ae-4d3a-b30c-c2be5cf38bf1 · outbound

This paper cites L., Holtzman, A., Fried, D., Liang, P., Eisner, J., Hashimoto, T., Zettlemoyer, L., and Lewis, M.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding L., Holtzman, A., Fried, D., Liang, P., Eisner, J., Hashimoto, T., Zettlemoyer, L., and Lewis, M

Reference 20

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.144544Z digest=sha256:c32602b3fca52757f51a3a757842ce4e495c7b569f534a872b615eaff483ca05

Observation 42bc14e7-837f-4981-ae2f-e558e01c5b3f · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Evaluating object hallucination in large vision-language models

Reference 21

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no resolver link, observed 2026-08-09T16:50:15.147240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.147240Z digest=sha256:6d77c2dad31660a305bc68497c1ece7de2bc584dabf3f45cb18778a9b670ec2a

Observation f2f7b31a-4d18-4e90-8290-223efc4d18af · outbound

This paper cites an unresolved cited work.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Unresolved cited work

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.149752Z digest=sha256:31356f57a2efc144fdce3d6a57672ce77d5f29cb0b8c7fe08dcd82309f71a043

Observation 7cd04f2b-55d4-4251-bfa3-1e94c0b481b1 · outbound

This paper cites an unresolved cited work.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Unresolved cited work

Reference 23

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no resolver link, observed 2026-08-09T16:50:15.152274Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.152274Z digest=sha256:a01a03b7434df9cf414de862d4716ce69a6f995159ef1cee73fc3416b939c5f1

Observation 19af4125-9693-4553-b5b5-2508646fe04b · outbound

This paper cites Factual confidence of LLM s: on reliability and robustness of current estimators.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Factual confidence of LLM s: on reliability and robustness of current estimators

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.154648Z digest=sha256:047a6e5c93828015faca05ca930dd4538aacce848aaa9a115c04591f2d5e9f8a

Observation eb33f9ca-18c4-4380-8200-1faa2d337257 · outbound

This paper cites Mitigating hallucinations in lvlms via summary-guided decoding.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Mitigating hallucinations in lvlms via summary-guided decoding

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.602364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.157991Z digest=sha256:54dba4c4fd82046eebff03811c0ae49adb76fbd839c93008488de52cfd92ebfd

Observation 6b9e07a4-5729-4dd3-88cb-a8da85573df1 · outbound

This paper cites K., and Sankarasubbu, M.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding K., and Sankarasubbu, M

Reference 26

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unresolved
no resolver link, observed 2026-08-09T16:50:15.160831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.160831Z digest=sha256:cca0f82f7bf4981b462601f6700ed6c19ff980f160f27139a249b41c7f1d46a8

Observation ca90f6d2-b82e-4565-b313-b48fc7a44d61 · outbound

This paper cites Towards unified multimodal editing with enhanced knowledge collaboration.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Towards unified multimodal editing with enhanced knowledge collaboration

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.593851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.164269Z digest=sha256:f59842c35e916d5b24b000f6be49639fb314070799af6f72d3275fb458dd88f7

Observation 63239e60-631d-4c42-8226-3cc63121f47f · outbound

This paper cites B leu: a method for automatic evaluation of machine translation.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding B leu: a method for automatic evaluation of machine translation

Reference 28

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T16:50:15.452441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.167657Z digest=sha256:46bb6cd2f04c90bebac34a2b112f5e710bc293aec6f77a4ad607a3c362a60836

Observation 280fb77b-1fc9-40c1-bd8f-972a00387d04 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.170831Z digest=sha256:7992c21675617cae61aa08ad7c70ba29ae441310b3fa3fdb5c32400e1bd813d2

Observation b40b92a4-a531-4f31-8158-c6f3f7042106 · outbound

This paper cites D., Ermon, S., and Finn, C.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding D., Ermon, S., and Finn, C

Reference 30

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no resolver link, observed 2026-08-09T16:50:15.174414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.174414Z digest=sha256:38c0c643137cf83e6a67f026501d49e73fea29d925349c487860687bc37a30cf

Observation 4c9b6e7d-2090-4b46-afb6-cb57434ea58c · outbound

This paper cites A., Burns, K., Darrell, T., and Saenko, K.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding A., Burns, K., Darrell, T., and Saenko, K

Reference 31

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unresolved
no resolver link, observed 2026-08-09T16:50:15.177929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.177929Z digest=sha256:700962269ec1286a679273e367cfe999f45b136a46a67259a917f6d8088f6f87

Observation 92aec232-827a-4f93-b172-6f0a6b53b4bf · outbound

This paper cites A comprehensive survey of hallucination in large language, image, video and audio foundation models.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding A comprehensive survey of hallucination in large language, image, video and audio foundation models

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.577289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.180734Z digest=sha256:943287ed92c35ca83b17b915d771083ac258f9ad7e6d4c1800bbd9636961b0a5

Observation d64597da-2ecc-4f2c-927e-b0d78dc229cd · outbound

This paper cites Gpt-4 is here: what scientists think.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Gpt-4 is here: what scientists think

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.569752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.183825Z digest=sha256:204ebb0e69e5ad38b56846b267e3ca72c20ccc9b48a7666df0aef6e2cf5efc9b

Observation 2bf73d00-c35f-430a-9acd-07c831357e95 · outbound

This paper cites Multilingual fact-checking using llms.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Multilingual fact-checking using llms

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.562794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.186681Z digest=sha256:dad9bdb9aa9cbe0da3733f4a16465a7ab5cc43c11869fddec5245d79c5c4867c

Observation 829fb95d-4d74-43fc-afd0-2ff670d26647 · outbound

This paper cites and Huang, S.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding and Huang, S

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.552482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b2f27379-716a-4c59-b835-c0102cceb5fb · outbound

This paper cites an unresolved cited work.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Unresolved cited work

Reference 36

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 75c05173-6c4a-4257-90b6-633186e4b6c8 · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Mitigating hallucinations in large vision-language models with instruction contrastive decoding

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-09T16:50:15.195666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.195666Z digest=sha256:d88024d72a29cec90fd5a6fd7f3793f7af7b2ee0adf69f0934c213e68936eef8

Observation fdf0bb9d-3c40-4c05-b9a3-24d0c0ef2bcc · outbound

This paper cites W., Lester, B., Du, N., Dai, A.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding W., Lester, B., Du, N., Dai, A

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.539429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.198071Z digest=sha256:31850d7c46cac186a0accc2a25d292962ba9f8f960fe159e6244c29b0ab8441a

Observation af55f200-63d7-4ff4-b1ca-f37f6356f377 · outbound

This paper cites On the road with gpt-4v (ision): Explorations of utilizing visual-language model as autonomous driving agent.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding On the road with gpt-4v (ision): Explorations of utilizing visual-language model as autonomous driving agent

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-09T16:50:15.200291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.200291Z digest=sha256:2d4075048703b4d63aa238194d3549763ac62ae2ddb9e35e178a1686ca9a3385

Observation bf961074-8082-44da-ac63-960dbd0e4f43 · outbound

This paper cites Transformers: State-of-the-art natural language processing.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Transformers: State-of-the-art natural language processing

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.522595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.203004Z digest=sha256:5a814ab8b19b172c9e9d10813a95a5a47995a8cc36a723d472c85a46baa88883

Observation df2c4c8e-199f-41f9-a50e-ebba216e2472 · outbound

This paper cites MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-09T16:50:15.206449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.206449Z digest=sha256:5003e7f890cbf34ba4be0c0cadbc667ce8aff7e58dd2e95ef2c6dfbf0cc77f9d

Observation 05757f81-8a77-4dbd-904e-40261877f39e · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.514173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.211754Z digest=sha256:a83aefa6a1a87a3edca7af3eee29f0e20b94e2d259437eebd2870766e8bd8b5c

Observation addb0823-f289-4e5d-94e5-e6afa40c5578 · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.504852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.214829Z digest=sha256:7e642b1c9340755448a121a83df0e654a56503ebb13f58065660a3f0288f5647

Observation 9f1b50f9-3501-4fa3-b3df-7a660e9a1357 · outbound

This paper cites TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-09T16:50:15.217582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.217582Z digest=sha256:e57f78d27ad604db94e9800d11b6023e93aae1b9170cdc1f8e350099b0f5c162

Observation 8b810425-0cc1-4ab6-8891-67be871babdd · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-09T16:50:15.220498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.220498Z digest=sha256:76cef291b680ad9527af6af12567bd7fee02bc8f4029a5b46f96e74df4de87ac

Observation 6a9ab826-3a57-4eb3-b916-7552cb729faa · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Mitigating object hallucination in large vision-language models via image-grounded guidance

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.495814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.223133Z digest=sha256:c92caa86c4256ac515b02e295256bb042dd15df9f2c86b93d301a261f27c330d

Observation 7296b114-2e35-4b67-8708-4c57e1429baf · outbound

This paper cites A Survey of Large Language Models.

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding A Survey of Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T16:50:15.225628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.225628Z digest=sha256:bbc98a8036323d2726d593daf820e23244ec5db44b2d82ac927d5a2252af5eb2

Observation e68d270c-91f7-45c8-afd7-da779d12db28 · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Analyzing and mitigating object hallucination in large vision-language models

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:50:15.487395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-09T16:50:15.229630Z digest=sha256:4a7d1fff484cd419268f1436f06a9ede2e5974b6cd11ed434c147922fe0bf908

Observation f81e2ef7-4b8f-4592-9067-8d3459ce9a60 · outbound

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

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding Mini GPT -4: Enhancing vision-language understanding with advanced large language models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-09T16:50:15.232756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T16:50:15.232756Z digest=sha256:67ce8cd9e767ee2bc4e1d7f3eb996372670d769e3ef20790fb35ef55af191782

Pith citing papers

Observation 8f64d723-9301-43ec-a40b-493d78edb947 · inbound

HTDC: Hesitation-Triggered Differential Calibration for Mitigating Hallucination in Large Vision-Language Models cites this paper.

HTDC: Hesitation-Triggered Differential Calibration for Mitigating Hallucination in Large Vision-Language Models Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:01:04.182670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T15:13:49.239474Z digest=sha256:c146522fe5276325c30239883ba1428901359253332ce49fd9ccdecd357df4e1

Observation 976f8086-1d7f-4fcc-aabf-da73def19b68 · inbound

GEASS: Gated Evidence-Adaptive Selective Caption Trust for Vision-Language Models cites this paper.

GEASS: Gated Evidence-Adaptive Selective Caption Trust for Vision-Language Models Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:11:15.203519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T15:34:59.318997Z digest=sha256:7c26a08ac9eb58b5b1daa787f1e1ee184e78730319b41888cfc18a89751a317c

Observation 421cb0c2-caf8-43a0-970f-6bd7432207c8 · inbound

GEASS: Gated Evidence-Adaptive Selective Caption Trust for Vision-Language Models cites this paper.

GEASS: Gated Evidence-Adaptive Selective Caption Trust for Vision-Language Models Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-21T00:43:53.563211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T00:41:58.198403Z digest=sha256:29c47535c513eaac8305f803f6bf6d4c0b90b8c71352e77ba996f5e2b6d2102b

Observation 502bbc9a-4925-4eda-98f7-772f86f106f2 · inbound

GEASS: Gated Evidence-Adaptive Selective Caption Trust for Vision-Language Models cites this paper.

GEASS: Gated Evidence-Adaptive Selective Caption Trust for Vision-Language Models Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-01T00:35:10.141999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-01T00:32:49.666202Z digest=sha256:5dd99be8dd47c4dfa625df1e1f6b4b6d6938f243139a87955edb9180b0cc3358