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Paper Citation Record · LEDGER

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling

As of 10 August 2026, this Paper Citation Record lists 88 of 88 outbound references and 1 inbound Pith citation observation for arXiv:2507.05056.

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

pith.paper-citation-record.v1
2507.05056 v2

Coverage vector

measured 88 of 88 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:38:19.660978Z

measured 89 of 89 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T23:51:47.724033Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z

Reference resolution

88 of 88 outbound references displayed

  • verified exact5
  • verified fuzzy37
  • unresolved43
  • parse uncertain0
  • malformed identifier3
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cde163f2-8c77-43a1-b3cf-0994f4aace27 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:18.543645Z digest=sha256:e69759d12ef4bbd4861b7cd76875534e07221492fc2bb5c56a717d78aa38ce86

Observation a1fb25db-3cec-43ef-906f-8fc625f13c61 · outbound

This paper cites Qwen Technical Report.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Qwen Technical Report

Reference 2

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source=pdf_text observed=2026-08-06T19:38:18.641082Z digest=sha256:682ed66494c79d130898b05af9dfa0a7657b598dc40174871a7aa0d62957ac7f

Observation 32146d21-d3c0-49b7-836c-928f63a46e6b · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

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source=pdf_text observed=2026-08-06T19:38:18.738529Z digest=sha256:6103408c0bdd1313729dbc4d8b0bc395e22072cde3494858beb31c6bf135215b

Observation abd1f3f1-8060-4670-9419-2bded2f1845b · outbound

This paper cites Audio chord recognition with recurrent neural networks.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Audio chord recognition with recurrent neural networks

Reference 4

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no resolver link, observed 2026-08-06T19:38:18.889260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:18.889260Z digest=sha256:a681e486d64bdf48055968f9ebd4990da17029f2df7ac1d3d7bf41a9022899f1

Observation a5f89206-c5b7-4a57-ae89-6a8068f7b646 · outbound

This paper cites Explaining a series of models by propagating shapley values.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Explaining a series of models by propagating shapley values

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.116024Z digest=sha256:79d1311c60500d922bbd53aad3e5c1403b40b1486ee317b43f98ffc8eacaa746

Observation 14a3c217-acfc-41a1-9175-0c4b255ad614 · outbound

This paper cites HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.235787Z digest=sha256:fc817b6a92593cd40045bc51dc2f2ba30cdc86bbed7a46d4965bfc3a08b67835

Observation 4eec48b3-1663-4ede-a27a-99988b8e0564 · outbound

This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.295473Z digest=sha256:778b2bd57d39c16495bd60fc0b68cd1bf9cde5a0f6b1b98cf8ebc9eae8cd3653

Observation 77c2f478-91d0-4563-8c17-358dd4ebcf98 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Mitigating Hallucination in Visual Language Models with Visual Supervision

Reference 8

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.305433Z digest=sha256:18ab88dbc965704ba30df19c6a7eb52dea2dc78356c7dce2c6c153a0e172c4fc

Observation b6e23cfd-04b9-40f6-b682-be1301f0a10e · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.310549Z digest=sha256:bc152e5b163982e1cf7f10688c8736d0d66067a82332aebf0a9e36221489a953

Observation 5adf8b47-d680-4fd8-9a0f-c9cb8648e60d · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.315314Z digest=sha256:6451a05aa81cfd9e1d514a93ada3a89b48327917d1d24d21f00bd71456f03aca

Observation bb014128-057b-4da0-accb-0fa9e84d5f85 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.319571Z digest=sha256:826688ba174e39276718a0aa910da68ecff9b8fa547483f6224e8fc36dea3f5a

Observation 27dec42c-0982-4fe4-8aea-80063af9da73 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.323992Z digest=sha256:0bd7c88239f2f03afb117f79b65740d56d3faf8fff7b7bff136d14ed66598398

Observation 9b05a7d3-e268-4b27-9fba-4d7c5a8afa63 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Instructblip: Towards general- purpose vision-language models with instruction tuning,

Reference 13

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.328013Z digest=sha256:2774813ae8f09206ca573ca6e180d6a79f1da3a2b4af05920655861150325582

Observation c9c02951-86d5-4b28-b4c6-f89920d25ef2 · outbound

This paper cites Discovering and Explaining the Representation Bottleneck of DNNs.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Discovering and Explaining the Representation Bottleneck of DNNs

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.336977Z digest=sha256:4bba25bfaa150937220234edd2c1e6157acafefe725b8efa1030e5ef5b21941b

Observation 4a22e055-b58d-4069-afb2-7158c7c8c8b2 · outbound

This paper cites Explaining deepfake detection by analysing im- age matching.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Explaining deepfake detection by analysing im- age matching

Reference 15

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source=pdf_text observed=2026-08-06T19:38:19.342129Z digest=sha256:74ac996335344602c11c426918693c09b6e07eac7e6176e62b128c2c50cbc116

Observation bba5652d-6683-4270-b8d7-0c0cee8a4b2a · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.346285Z digest=sha256:b7da10d344458ad62791fe6111231bedc9f249e7c351bc00f395c13c41e0305e

Observation de86c1ac-25fa-4518-8f01-552187d3beb7 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Multi-modal hal- lucination control by visual information grounding

Reference 17

Resolution
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raw_fallback, observed 2026-08-06T19:38:26.342045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.350419Z digest=sha256:f0f1cb6960d48daef2809996a56a9785fa34a6eae1d399d22ed01c15bd14cc90

Observation d0b5b00c-a6cc-499a-95e4-7b5538186ba4 · outbound

This paper cites Shapley val- ues for feature selection: The good, the bad, and the axioms.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Shapley val- ues for feature selection: The good, the bad, and the axioms

Reference 18

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raw_fallback, observed 2026-08-06T19:38:26.007838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.355250Z digest=sha256:2d512c284caf8c4905224b945b85a0842985808bc0f94fd7ce1b50c2dc645831

Observation 922a97d6-8cd5-40e9-a4f3-86892197d85c · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 19

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source=pdf_text observed=2026-08-06T19:38:19.359965Z digest=sha256:d63534aa7ef8d930176ba18461533cbbf6cab1ac5c93955253387d81b4cea994

Observation 77f4446a-42ab-4603-9988-178a70cc16fe · outbound

This paper cites An axiomatic approach to the concept of interaction among players in cooperative games.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling An axiomatic approach to the concept of interaction among players in cooperative games

Reference 20

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raw_fallback, observed 2026-08-06T19:38:25.786723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.364795Z digest=sha256:9429842f6f5011e41cf833fb3693f46424cf4d63ed05fc852d8efa7cb08d2b8c

Observation ec0d1c72-e24f-42c8-bdae-6eaf36412b51 · outbound

This paper cites Sequence Transduction with Recurrent Neural Networks.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Sequence Transduction with Recurrent Neural Networks

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.369136Z digest=sha256:aa15003fa26ffddf8030a5344a6ead43c6bec16a90bec5289411375d45924bee

Observation 187b7394-8d7e-4911-a615-871cd4906a1c · outbound

This paper cites A simplified bar- gaining model for the n-person cooperative game.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling A simplified bar- gaining model for the n-person cooperative game

Reference 22

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raw_fallback, observed 2026-08-06T19:38:25.472728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation fb62258b-cb84-4f16-b3d2-7e649616f458 · outbound

This paper cites The curious case of neural text degeneration.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling The curious case of neural text degeneration

Reference 23

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raw_fallback, observed 2026-08-06T19:38:25.162147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.377534Z digest=sha256:559d1dc44aab19d14dd8da0cb03c1d7d651413c88156ce4fc41c33102bbae895

Observation 3be5026c-c421-4e8c-b802-c24f8f2571ad · outbound

This paper cites spacy 2: Natural language understanding with bloom embeddings, convolutional neural networks and incremental parsing.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling spacy 2: Natural language understanding with bloom embeddings, convolutional neural networks and incremental parsing

Reference 24

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raw_fallback, observed 2026-08-06T19:38:24.881163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.381831Z digest=sha256:7344078d05b154b18e1f1a4ad16fa0947793697f424b8f766f779bfe95c795ba

Observation d2482827-9a6d-4da5-bc0c-2d06dcbf784d · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Opera: Alleviating hallucination in multi- modal large language models via over-trust penalty and retrospection-allocation

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-06T19:38:24.669459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.385888Z digest=sha256:6455d161337fb8c87c1b45a05717a424887f54dbd5664d40660272f84dc033c0

Observation c0a21d6c-fcd0-4947-9f66-03d72cb4917a · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 26

Resolution
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raw_fallback, observed 2026-08-06T19:38:24.493981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.389940Z digest=sha256:0bc8225d01f84e9bf7e8a6acd73be1cc4161559510b0bde60d23255bfa216be7

Observation 85fe5ffc-b528-4464-a4d3-eac8446b038e · outbound

This paper cites Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.394394Z digest=sha256:82b119800ccc1e3010e8a3fa0b98d112afbe9387a8666522487de94d846a202c

Observation 7d197cd5-7f59-4a43-988a-e9eb4e90aee4 · outbound

This paper cites GPT-4o System Card.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling GPT-4o System Card

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.398916Z digest=sha256:5c84a418093a70ccd576dfe98e1cae9a0937e12578ed0e73b32a0b12db6396b8

Observation ae821b85-f618-48d4-84dd-01223ad74e82 · outbound

This paper cites Vcoder: Ver- satile vision encoders for multimodal large language models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Vcoder: Ver- satile vision encoders for multimodal large language models

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:24.300730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.402801Z digest=sha256:15c458cc01aed2672e9b00f0ea64de77cea9e2fc0be04962b139255b1fdeca4a

Observation 9e1fb101-0060-4cb0-a6ea-95f24be9a26a · outbound

This paper cites Hallucination augmented contrastive learn- ing for multimodal large language model.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Hallucination augmented contrastive learn- ing for multimodal large language model

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-06T19:38:24.043409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.406874Z digest=sha256:8f55497e7ea6bf24966e1b5d8e25f326bfb39287d738b1f32bfd8ac01faac021

Observation 650fe551-ea2f-416f-8532-9aa34c0f1079 · outbound

This paper cites mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.410901Z digest=sha256:b88663365361e6a621f1291f2b8f3d6722ab2ea262752c3914ef499a35c139b9

Observation 8b304bf2-f282-4b24-8413-fbb69e49c2f0 · outbound

This paper cites Contrastive Decoding: Open-ended Text Generation as Optimization.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Contrastive Decoding: Open-ended Text Generation as Optimization

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.415802Z digest=sha256:b9b4b0926cc45fc6140886e1ab72a09a06a577276f3188b289f722f416aa1d78

Observation 3fff2933-8b88-45dc-8687-bb999c88e654 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Evaluating Object Hallucination in Large Vision-Language Models

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.425125Z digest=sha256:fda13d4530a73803954ebc5ea14bf24df6260e21d686b00a5dba696a783fa72c

Observation 73105847-2c71-450b-9247-d91b87a189c8 · outbound

This paper cites Microsoft coco: Common objects in context.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Microsoft coco: Common objects in context

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:23.825026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.429406Z digest=sha256:60f6ab5aabf6ae4e32b0f5ed26bd078d1f63c7a585b596fd32c3906bc142bf34

Observation 4e80fea9-ad4e-464c-9660-ffea4130c2d0 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.434030Z digest=sha256:a7e8064b29ac434bb831392bbc298f1d0b5c93cff53a2fe6674af4e725484368

Observation aeaffdb4-21ca-48e3-aef6-f3b0309677d1 · outbound

This paper cites Llava-bench in the wild dataset.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Llava-bench in the wild dataset

Reference 37

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raw_fallback, observed 2026-08-06T19:38:23.638230Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.439024Z digest=sha256:525ae8196d71cee10729ecaa95da688c1f203ce8d5fcd01aa9140be784dd1341

Observation b0b1efb2-7dcc-450b-a7b4-f8a51466909d · outbound

This paper cites Improved baselines with visual instruction tuning, 2023.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Improved baselines with visual instruction tuning, 2023

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-06T19:38:23.365231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.443488Z digest=sha256:f53f8fa7d0982a7ec336dd078750944d5b81b968d3ebb99a5b0f4970872ba4f8

Observation 81672b28-54e1-412e-8f76-d4d9f27341a0 · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling MMBench: Is Your Multi-modal Model an All-around Player?

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.448410Z digest=sha256:10d2a3fcc271d2fcbe61014d0d40e4994a12908f93f7383012f5518636ac9176

Observation 6d962263-043a-4890-9fac-f8d2c0a7c1b6 · outbound

This paper cites ConVis: Contrastive Decoding with Hallucination Visualization for Mitigating Hallucinations in Multimodal Large Language Models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling ConVis: Contrastive Decoding with Hallucination Visualization for Mitigating Hallucinations in Multimodal Large Language Models

Reference 40

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source=pdf_text observed=2026-08-06T19:38:19.453361Z digest=sha256:654a71e2ca8e773179f07a72df289d08d1da93a82005091a561970f272c3b680

Observation 9e4ebc1a-37c7-4fcb-8372-16f4320294f6 · outbound

This paper cites ALOHa: A New Measure for Hallucination in Captioning Models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling ALOHa: A New Measure for Hallucination in Captioning Models

Reference 41

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verified exact
local_arxiv, observed 2026-08-06T19:38:19.955781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.457909Z digest=sha256:4f3d1ed8852e983d2a52f55f716a42e1de32a7c730018c8edd097caf1718a542

Observation ec5bf09a-d69e-431f-aa31-6fb443969130 · outbound

This paper cites Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.462703Z digest=sha256:378b9f3adef540dcc319b62cb739b25e2e339a9f4e8eff39a2ba780ac2b808de

Observation 29eeb48a-e5e8-4c2c-a46b-9dfcece3af37 · outbound

This paper cites A Unified Game-Theoretic Interpretation of Adversarial Robustness.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling A Unified Game-Theoretic Interpretation of Adversarial Robustness

Reference 43

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verified exact
local_arxiv, observed 2026-08-06T19:38:19.917414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.467577Z digest=sha256:e4c686431f8b09499b2528ebe002fe34945a10d3161e4478b660dcb63a71e1fd

Observation f7b76607-d9c0-49f4-a0e9-d0350ac9c7c2 · outbound

This paper cites Can We Faithfully Represent Masked States to Compute Shapley Values on a DNN?.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Can We Faithfully Represent Masked States to Compute Shapley Values on a DNN?

Reference 44

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verified exact
local_arxiv, observed 2026-08-06T19:38:19.895832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.472048Z digest=sha256:66b437db0824db0423295df6a98f01633d268180694598e30075a201c8036ac9

Observation f529a361-e618-4838-bf63-674bd14f7232 · outbound

This paper cites Defining and quantifying the emergence of sparse concepts in dnns.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Defining and quantifying the emergence of sparse concepts in dnns

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:23.153811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.476497Z digest=sha256:d3c06a00af6aaf92824031cf66fd1f1c2b35792499367818487cb06cd8ae99e6

Observation c7583dc6-9f33-4fa0-b27a-04ca6a6e529a · outbound

This paper cites Object hallucination in image cap- tioning.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Object hallucination in image cap- tioning

Reference 46

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no resolver link, observed 2026-08-06T19:38:19.480573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.480573Z digest=sha256:0c1c5a56ea33091f59da41348de95946c2ad897ea74b5f635a0b6c7bc509916f

Observation bf777500-2db8-4457-8708-d6c7a1881bef · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling A-okvqa: A benchmark for visual question answering using world knowl- edge

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:22.623496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.490255Z digest=sha256:fa5ec7f3d82cdea87d3fd6825d46a5af19b127f07a6f72a39117b28324065da1

Observation 134f230f-6abd-48f1-bc93-ccac0a28ee95 · outbound

This paper cites A value for n-person games.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling A value for n-person games

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:22.352688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.494518Z digest=sha256:b025d61af051e10a87bee1316b6eee512f23e45ceb928ed1270a96d0c724b6c8

Observation 4b4ff39a-1a9f-4ecc-9496-2c30b67cc78b · outbound

This paper cites The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.498886Z digest=sha256:4406a485bb42ddfea13c5cb303f911fff969f6aca57a7ff89b4709d1c40c80ae

Observation cc52176b-9033-4924-9e8f-ff9bf702d255 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.503233Z digest=sha256:098adf62ed4f7033b24d1fb99447bd99e012eb85f7410ae4b2cb19fc4e8591a9

Observation b3985708-eed1-4484-be13-cc06e5b71596 · outbound

This paper cites The many shapley values for model explanation.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling The many shapley values for model explanation

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:22.121952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.507571Z digest=sha256:2a19a5907bdf69cbced08114f081f35389cf282807d6a0d92ef3e6099e8fea4d

Observation 483ef97e-44a0-4c56-a920-789bcbdf22de · outbound

This paper cites The shapley taylor interaction index.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling The shapley taylor interaction index

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:21.928008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.511674Z digest=sha256:10ecf127ac2978a253fecc6c9df05c5c97ac878fd7b1cd5ad578974b17cb5984

Observation f7bbec4e-1e31-4cd5-bee2-e9a28e5dae72 · outbound

This paper cites Sequence to sequence learning with neural networks.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Sequence to sequence learning with neural networks

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:21.648284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.515913Z digest=sha256:59fcb26e9f305b22fc6c5095cab96d6722c3e6af51ac7aac25ff286338b33508

Observation ef6b4625-eaa3-4d29-93ec-b0a1065b24c1 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.520881Z digest=sha256:9503cb1a442c9f8eb2e05dcde5f745bcba51320028662b9b1fe2376428f6760e

Observation c19d4d64-6667-4f9a-991a-0ced4f2edaf2 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Reference 55

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.525397Z digest=sha256:bf5002a6f14bf130c24f0a2eb896e85cf5c48c9edd48e6807b88a21b18e61663

Observation 4a4c0d5b-4252-49cc-9412-e49e25669e1c · outbound

This paper cites Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View

Reference 56

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verified exact
local_arxiv, observed 2026-08-06T19:38:19.809275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.529779Z digest=sha256:57e145c9e65e598dd689c3f7ae419be794b2b3bb38aa053ad90bd774a790c3f4

Observation 318c25dc-19f0-48ea-b975-02a146fb879c · outbound

This paper cites A unified approach to interpret- ing and boosting adversarial transferability.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling A unified approach to interpret- ing and boosting adversarial transferability

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:21.453645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.534455Z digest=sha256:9a1cbefa164e4b4fdd85279adc65cf84c20c77d695700f1c20f109ed1734bf83

Observation ca4a43e2-58b5-4920-8419-6ad8d5c82730 · outbound

This paper cites Interpreting attributions and interactions of adversar- ial attacks.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Interpreting attributions and interactions of adversar- ial attacks

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:21.177952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.538795Z digest=sha256:2a6cf1df3ab2e32721ecd486187689f525eaec3639d34769556ad70af9046456

Observation 77c0045a-de0e-4004-8161-4ae7263fe224 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models

Reference 59

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.543126Z digest=sha256:fa69b53c7de6fdbc023d55b931bc3e77ba2dee73b2ffbe834a6f7279174f4034

Observation 291c248f-be04-408f-ad8b-2f4e79a1109e · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 60

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.547606Z digest=sha256:8107ab432c0883ff42cc82e49bb45f59da869dcf46294073bdcc789d956d532a

Observation 2012884b-c9c0-4439-b567-4e795a5af1ff · outbound

This paper cites Towards understanding the generalization of deepfake detectors from a game-theoretical view.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Towards understanding the generalization of deepfake detectors from a game-theoretical view

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.921201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.552093Z digest=sha256:8c84a4504c1cedc0477dbb0fd3d58d3befe3a64728e1f1a48e4ac972c5737af3

Observation d2164764-afa4-44f7-93a9-57ab4100f894 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

Reference 62

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.557416Z digest=sha256:df447375c35bc5d0a410c5ca919e73dcf6e3b31e1c4223061310dc199b9e8efd

Observation 1249e4de-e633-47bc-a3ec-c0384cf3736e · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.772787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.562593Z digest=sha256:808158a24134874784b420849d35c1d5278c6fd332ab26617d70a6f36d68a861

Observation 050f154d-3fe5-4eaf-b8f7-2c0f1e30488e · outbound

This paper cites Modeling context in referring expres- sions.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Modeling context in referring expres- sions

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.724467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.566697Z digest=sha256:ed22f450ba2f7cd39938ee3de47e2b96722fb4e05ed07a0b4d39d274ba20e8b4

Observation 0161e570-e149-4c75-8a73-c60890974455 · outbound

This paper cites Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.689823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.570923Z digest=sha256:1053d1e967bb7cfd57a0ec40bb5d4d13ed86af0beff55ab5f379592db8b35c52

Observation 96b9cab1-d2a4-41a3-aa61-3ccb702988e5 · outbound

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

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective

Reference 66

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.574901Z digest=sha256:93f451c277bdca5038621fa26fcddf0dfb345cec9f35c8e171175bdff1296c8b

Observation 945083b6-f25e-4346-8cda-b30ad4879084 · outbound

This paper cites Halle-switch: Controlling ob- ject hallucination in large vision language models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Halle-switch: Controlling ob- ject hallucination in large vision language models

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.669545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.579844Z digest=sha256:501f3f62aff3df4c11a3711cffff669e7b67892c69ee4eb920ed6f4849f71bae

Observation f0ae7641-632e-49fc-a02b-7846e89581c5 · outbound

This paper cites Building interpretable interaction trees for deep nlp models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Building interpretable interaction trees for deep nlp models

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.653107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.584614Z digest=sha256:336695a1e042f2d74582ad5446caa2db663d87f9eccbb14c3d748c4db1c2b1cf

Observation 97bc30db-ad68-4f09-9ef3-52995a9da03f · outbound

This paper cites Technical Note: Game-Theoretic Interactions of Different Orders.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Technical Note: Game-Theoretic Interactions of Different Orders

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:38:19.724425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.588776Z digest=sha256:4054d7c695080c80f7ca1943327fb05124bc2283bd6237f8ddaf970303c03855

Observation ea42423c-a0f1-4822-a4c0-89f4b104e7b0 · outbound

This paper cites Interpreting multivariate shapley interac- tions in dnns.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Interpreting multivariate shapley interac- tions in dnns

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.637752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.593003Z digest=sha256:0b75f4ca713370660dbef225e99ecbccc218630e140061c796c3bfcba5efdde5

Observation 624be49e-5c6c-4b77-91a8-fce28c0273bd · outbound

This paper cites Explaining gen- eralization power of a dnn using interactive concepts.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Explaining gen- eralization power of a dnn using interactive concepts

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.622141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.597266Z digest=sha256:011322cb5e880511db3b39ceda9f8dc29aec5acd9e245d8bfe9ab89b499c1269

Observation 6e02966d-90f4-4502-aaf9-660001192938 · outbound

This paper cites Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.601377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.601377Z digest=sha256:c1a01b08d82b62a4dca345a01a89a26d7e076c268bdb049827822f8c44ed13c4

Observation 6f633e1e-5a50-4c4b-bc46-ee9819a304bc · outbound

This paper cites The Polling-based Object Probing Evaluation (POPE) [33] utilizes images sampled from several datasets, including MSCOCO [35], A-OKVQA [47], and GQA [26].

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling The Polling-based Object Probing Evaluation (POPE) [33] utilizes images sampled from several datasets, including MSCOCO [35], A-OKVQA [47], and GQA [26]

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.607116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.605809Z digest=sha256:33957a8a33d1cb94202d7ab8022ed7a5e87b6ad131dc154aeb5ec84cbd6ab49f

Observation c0db2e3d-7c47-4cc1-a523-b4e07dd744a7 · outbound

This paper cites As shown in Tab.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling As shown in Tab

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.592658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.610211Z digest=sha256:30e7626042536395bcb8c86b72881cf289e95aff60fac1b1be4371a748004848

Observation a5f312c9-410c-4083-aed1-bceda856df19 · outbound

This paper cites an unresolved cited work.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Unresolved cited work

Reference 78

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:38:20.579002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.614489Z digest=sha256:84bac72578556432cfeceb61f5d7eb9abba02efc62ba8bb2c8ff144b87478cc3

Observation 2428d4a3-430c-417d-9f43-2122bc72bdff · outbound

This paper cites Through experiments on CHAIR [46] and MME [19] benchmarks, we analyze how the interaction guidance co- efficient k affects the performance of INTER.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Through experiments on CHAIR [46] and MME [19] benchmarks, we analyze how the interaction guidance co- efficient k affects the performance of INTER

Reference 79

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T19:38:20.565237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.618717Z digest=sha256:6affad2ad80e995a5071af065bba12e3136245184ff3e64204d01493c4926147

Observation b98024fe-4daa-4488-939a-18b2d5b3dd89 · outbound

This paper cites The results, as shown in the Tab.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling The results, as shown in the Tab

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.549878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.623097Z digest=sha256:c4d891b49f771a41315830572d8f3319e31e32a4e11f3177cd559ef0cac1b2c4

Observation ddc901fa-c9c4-4dd7-ba52-e189e078691b · outbound

This paper cites As shown in Tab.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling As shown in Tab

Reference 81

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T19:38:20.534946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.627527Z digest=sha256:9f5d5926a9f4b703b756dc6d4d9e7f0907f68eef82ddef66ecfa3fd2b76ffca1

Observation defe6cd6-866c-4951-8aa3-a9cd43e97b6e · outbound

This paper cites 10, 19 and 20.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling 10, 19 and 20

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.519750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.632418Z digest=sha256:f14cf4236f0ceedc71c096793ae01480829766fe719dbea57f0f8f5cea0f85e2

Observation af3be004-b5ae-4e4c-a261-b1d82dcf65b4 · outbound

This paper cites 12, 23 and 24.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling 12, 23 and 24

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.504515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.636734Z digest=sha256:138f6fca22977247c3ef07b8a4913be8ca155df131a7da395c94d4301fc2d6ee

Observation 8de149a9-a5a9-414d-a7db-9902c042dea8 · outbound

This paper cites 8 to 13, 15, 16 and 19 to 26, we demonstrated the effectiveness of INTER in correcting the Greedy Search across various benchmarks.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling 8 to 13, 15, 16 and 19 to 26, we demonstrated the effectiveness of INTER in correcting the Greedy Search across various benchmarks

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.488666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.640857Z digest=sha256:f059058647d02b5382ed78abe10c8ed2ee9c8253d73ed563c5075fdc3c5fa305

Observation 89c1f77e-73c8-4eb8-bcf2-9fbf0235e02b · outbound

This paper cites an unresolved cited work.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Unresolved cited work

Reference 85

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:38:20.472206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.644875Z digest=sha256:c9c8bc280506a82ebb322bd2f18cb4fbdc9e98fec47f0c84133c50d436448df9

Observation 37e6d830-d325-497c-b8e6-b96d45aab416 · outbound

This paper cites an unresolved cited work.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:38:20.456978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.648885Z digest=sha256:b231732948896220f0aaf386e77621fe71de36198cc228e00523ffe6f8da08fc

Observation 4b41057f-1334-46b1-aaad-5288789c308d · outbound

This paper cites We conducted experiments with M3ID [17], Ritual [59] and SID [27] in Tab.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling We conducted experiments with M3ID [17], Ritual [59] and SID [27] in Tab

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.441900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.652910Z digest=sha256:138124962c8f71fdb88ce6ee77dc4c00f1819bf85a97fa5463a93067064ad1fc

Observation 92dbc7f1-a87a-49c6-844f-70792efc36be · outbound

This paper cites We conducted experiments with DeepSeek-VL2 [60] on the visual grounding task.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling We conducted experiments with DeepSeek-VL2 [60] on the visual grounding task

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:38:20.427414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.656842Z digest=sha256:9cac13527e3133783a427b88d864f422a755e47d1ce929a9fc2d1827b5369651

Observation f7ea1276-1890-405f-8bde-6650a8abbb3f · outbound

This paper cites The value range of I(A)yt could be influenced by several factors, e.g., benchmarks, LVLMs, etc.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling The value range of I(A)yt could be influenced by several factors, e.g., benchmarks, LVLMs, etc

Reference 89

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T19:38:20.412188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.660978Z digest=sha256:667e74cfbf03341abda707bbb1fa5d6ea73565061e73e982ef82e7111fe57a27

Observation 9d487f5e-a3a1-4ef4-b53f-64c24dd8b809 · outbound

This paper cites an unresolved cited work.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Unresolved cited work

Reference 2018

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:38:22.871959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T19:38:19.485115Z digest=sha256:fa4f1a5b3e2aae974b6e82cb24132febc03b402e8eda145693f1bb15e7544197

Observation 7d3728dc-8d71-4c22-b751-2ea4a757c123 · outbound

This paper cites an unresolved cited work.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Unresolved cited work

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.332718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.332718Z digest=sha256:d58f6abaae4064edce0a5a21420743c635bc43741e574b11f9a3be90095716e8

Observation 4feeb5fa-42da-4d45-8334-fdff83141b03 · outbound

This paper cites an unresolved cited work.

INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling Unresolved cited work

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.300877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.300877Z digest=sha256:30db5e918795834a8130bf668935ce95467e1e8a1a8f564bed9830771332f8f3

Pith citing papers

Observation 77c88cd2-e7eb-4675-afed-c9d9752cefea · inbound

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering cites this paper.

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling

Reference 272

Resolution
verified exact
arxiv_id, observed 2026-05-09T23:54:45.759084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-09T23:51:47.724033Z digest=sha256:b449dee42b683ade68e383d35b8e17139f2ca861bdd6ee4b61f63778ad9ccc2a