Pith. sign in

Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:18.543645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:18.543645Z digest=sha256:d9ec961bc0436c1815434bb49f4a4285c1350fe8415243ca4b9fc9df7c6ca323

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:18.641082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:18.641082Z digest=sha256:7adf3dcbc8e833d721ff273d1c1c04085713cb1cf381e95909be8cd47451f064

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:18.738529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:18.738529Z digest=sha256:f18787d41431b9d6e2776ae610a181a07e804a1683cb703e6e3ba1782deb8d6e

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

Resolution
unresolved
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:b8cea99bd55b0fd41669e93ac2daf1bdd53da04c2fce1ac19fdde333b05f165a

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.116024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.116024Z digest=sha256:8e098f187d442fb877bf903091966668baccc3b6926400c1dce833e8514c579a

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.235787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.235787Z digest=sha256:82d5a71538eb94ba5b957259c1f3fb6738733ff276d848e60fd24c29a82e759a

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.295473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.295473Z digest=sha256:5d6df455ecdb9377faf383756674fae49062540867d42cfaae7d17c181a05bad

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.305433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.305433Z digest=sha256:43007b113440adc1b52f5324e7b3c706b26428b473264b69e76b3a8e258ceac6

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.310549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.310549Z digest=sha256:8e516784f12e406cbb092868f248e22bc39cb026df7efe7899d4bbdfc136a6b6

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.315314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.315314Z digest=sha256:017febf180cfc2e4bf06cfe78f50165cb6dffce8d9e0e47a40ad7d7ef330ce5b

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.319571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.319571Z digest=sha256:153896339105080f8df7657ad8ef365ade502d1c0437356dc4dccd124c69dec0

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.323992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.323992Z digest=sha256:17bcb8f77034a2ee32ff75d571ac6fec9efff31deb4892429747a2e204151a60

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.328013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.328013Z digest=sha256:4ee7857438a6a0050d7202368bf4a903ac81126cdf159d4d13eaed734615c3d0

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.336977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.336977Z digest=sha256:8836deb78a6bb8ae169d81188c105311d56278d52aaac46a1c005ee64afd75a0

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.342129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.342129Z digest=sha256:ecf7cd7894f83882bd41454a68c2ac00c5b8f9569cfea466ae4d84d13c2488e3

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.346285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.346285Z digest=sha256:40d7a771b212cc6f0ef3b706ae1f18a6cf43fa0828a1d76d548249ef01a29ef7

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
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.350419Z digest=sha256:b08c9b3a2b503c54fc4d99a3e4564298e2f678808084b72b3d831c86705352f2

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

Resolution
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.355250Z digest=sha256:75c95fb244bc48c51f8c4e2c35eb9d21213df6c128fbed868a595bade47267d5

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.359965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.359965Z digest=sha256:12988887bec6dc6f1ee4c8ca44397d7cf69a6629e30d921c320b4198c0574a7f

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

Resolution
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.364795Z digest=sha256:9628962d8254b8715e8d25f4e6ff41fcf269eb4a9146d0045f4bf7d1bc23cf48

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.369136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.369136Z digest=sha256:6c0b61a605afc4d9ba6aa88f12ebfbff5ca8944e0f943473c7526610795311fc

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

Resolution
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.373583Z digest=sha256:36bdfa85b5c9db17046564cd893674beb3f36798e8f7603926a517d9435927ea

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

Resolution
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.377534Z digest=sha256:829aa1e34f6eb74a8a13cbcc647a975bd6856eea083211bbe41d911cf4c5f42e

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

Resolution
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.381831Z digest=sha256:4a9f800df753b6595e52a3f5d94e2ba1c20480091b6afc35d9ee15b5042c3f02

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.385888Z digest=sha256:45f6b8d803f6239713edd2a038f8a8e14096e849c086cf83a2cbba7272660418

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
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.389940Z digest=sha256:b5daa577f122bacae624ea853a8687afdbc1a2d2487fa434a6e7295d924d84a7

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.394394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.394394Z digest=sha256:e2b49bb5a41dfdd7c4026c60225ac351cdd7208ccb0702f40ab64d50be5f69b2

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.398916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.398916Z digest=sha256:2fba4b1e6cc22de12046a258554dff6b2587a0b175af7a739de85da2dabf68a5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.402801Z digest=sha256:800e87e637645820a7152c395deaf891d7d2e8a352bb8a4180dba845a1664065

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.406874Z digest=sha256:77245cd8444d8eef07b0f980e88ddcbf7dd4fef4d7fa1a6fdf5d7aede4758c6a

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.410901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.410901Z digest=sha256:5d2b57e9ce4b06c1a7e1d1987cf179eff2b1a45ad1900d1f99c379ae41560398

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.415802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.415802Z digest=sha256:8d2ce2ebfb6cd0938d5272c3ea80f85152d426c5bab51f65880185e0a6de8346

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.425125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.425125Z digest=sha256:f0112c5ac6fb21e288fff9f9ecd145af1a66eb58fbeb51b8b3ad49c8e9c878e7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.429406Z digest=sha256:3d4d55647fe88d632092023faa47fa04bfebb1c1f70ef6c6e36831dcb07c269f

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.434030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.434030Z digest=sha256:9ef835f8827f187b9118b273e6b6083057f76b25c2b41e623ce13ab4be994dc2

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.439024Z digest=sha256:fdd257f451e2320c7ded8f538ffe98977914dfb008c4ca79fec6d498f1b1554c

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.443488Z digest=sha256:dc41e20ce0be1a152a8b631b861d2d95c5c987a218fe3ab68b4979d016411dc2

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.448410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.448410Z digest=sha256:edd65da4164e28b832b8ebca87466fac666ed2519cd9183fbeec57a7e5ca2433

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.453361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.453361Z digest=sha256:011055dd4e813458c7e3214843a12a39b97bf99c539e7240669d6a9ad3bd56e7

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.457909Z digest=sha256:e8b0c3014ca1ce110ab378d14e3e494b14d68aa96d35dc88aebfa7e95a62b845

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.462703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.462703Z digest=sha256:3aa8efe63640784bea82445fc4fc42f918a562fd463f1889e1901ca739cfb4fd

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.467577Z digest=sha256:0a1160901e047babc2d85506b5db2ba30d5dff7b7c8e5629144c04c06584e2dd

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.472048Z digest=sha256:1aaacd403f748df7a4e0b96c94bdad0f91f5307502763c875a4f322645d31721

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.476497Z digest=sha256:97df9f300664bcda5f0a1e214f0ebc9de8bec0163d81cb60f6c2e418cf7d6496

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

Resolution
unresolved
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:f097124c481dc2977e16cd720d15c1077774c0448f5cac662efbc6082e6c5adc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.490255Z digest=sha256:d43e2667db2af3e849518691ecd3965540a05c20a63dad2c114918b8ec96eb24

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.494518Z digest=sha256:6c364db7a5a5ad83912689d8ed88da20bc90472b66f7fb64e179913c084ef95a

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.498886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.498886Z digest=sha256:bf05cb83afd4849431fb6bd48ce07bae3830937950e53d9191e008688b90d8e6

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.503233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.503233Z digest=sha256:3f719532f1bb13c3246e9c393d5801f5ae4dff8a983bc2c3cecd8d8d036a156c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.507571Z digest=sha256:2dabd728c6d6110566c51d963d54a4bfb97869a63df88bbf81823539768b4619

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.511674Z digest=sha256:714f4a426ae867c17a0895d580cf8a1f98e04f22879e5a146d185bc085b08c77

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.515913Z digest=sha256:5d9842e6d28ca860a05ea54bf6fa006847e3253b000b7384a540af4a2a9d617e

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.520881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.520881Z digest=sha256:d3370275ef0dca3ed745cbc219bd50914ea00228e09dd134dcbc224406b2e844

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
unresolved
no resolver link, observed 2026-08-06T19:38:19.525397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.525397Z digest=sha256:458e05407e375b08e34f12761908059fa1f9b244348a69b11be1eee9d0070a92

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.529779Z digest=sha256:dc6eae7ded953388551a72f59b222b1a9cebd3580545362da21abe55658f01d8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.534455Z digest=sha256:3ee855b751b8a2ad8017906858f4aa2bb7a37d4ae858bc2c2ce96914e7140586

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.538795Z digest=sha256:0c1196b7534c0adbaba7d58cb5e8c1ea3a31cd59a605213a456116c2699dbc22

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.543126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.543126Z digest=sha256:18b008ccfa26a8e3adbb7231a1dc999ff9838c079a35faa508b38c703990c494

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.547606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.547606Z digest=sha256:0024f79ac4e6242785609802ea77f433c04d929c997dd402df79a3772e47f175

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.552093Z digest=sha256:df8dbb2b43ea56cdb2811bada5ee09f6b2000a527757010b840678b71eab7089

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.557416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.557416Z digest=sha256:bf5179bb2fecfc4d8b9685bebb072e9b5271d1f19e10fb775e257d19ea9223c4

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.562593Z digest=sha256:e64ed60f5c2a045eefcbc32ecd79b88793150b6405b1f2538578d486b4f598c3

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.566697Z digest=sha256:0a0d82594a1b892a0cec68b8d6ae4de27cfe34119a14c421f5121574bcd730ab

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.570923Z digest=sha256:144e4c733cb4161303b9471e3440c6345374a2bb55edfca41395af7221f07e3c

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:19.574901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:38:19.574901Z digest=sha256:37f482a9bb2e4f50b98eeb5d5b1ffba9b68b34dcea561ac74b368e28a754e0b2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.579844Z digest=sha256:35e6ca708967b0597e388f49413ed7b4201fa2eef0d51812bb30016ab755b70f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.584614Z digest=sha256:d236e81e5a69dd44650d8ef8ec5009c756be37e90af6706afcbfa18926b4f721

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.588776Z digest=sha256:39d51a8980703d650f96bb09ca330b890c1c2d6fc2d0598b4178362ff37de053

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.593003Z digest=sha256:74e0c37c98702411ac865e91868ee8d71089bb3e1f5bf5eaef2af1ea393faa40

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.597266Z digest=sha256:643b7a0b1f33f70465352c60bf19f53300e991e6bf81ff862c2a59753a7be30b

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=sha256:4d2824d3cd22e229e5d7da4de7b0f00afaa576735f03984ed93c4624e48f5c44

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.605809Z digest=sha256:f26106a53e3e81a8c7e3e5ce6d83234ae26265814f851e1b5ca81b2308bd2e31

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.610211Z digest=sha256:ad65b6d240e7b71391d3a03c60007d3413336b3c2710231b23edf68fb0b0a0b3

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.614489Z digest=sha256:16f610b98fcdcccb0510f3fdc280bd2e74c190d8ba84d9fe3028630f30a11192

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.618717Z digest=sha256:ecab0f79dd08f51d465bbfd18f7ceefaf8d18e3bf5bcf475aa16e364925b0e7a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.623097Z digest=sha256:e07d904dab391fe325079f781ad7aa36c90d5eaccc86135977937a694bffa9cf

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.627527Z digest=sha256:ef67d3d0de20c75db26c413b213126acb362763daf5c55478233e233a3bead20

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.632418Z digest=sha256:8173fdb3ba1cabd9b9ba5dbc289fd964232610639c35f176095f3af65e7df1e9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.636734Z digest=sha256:6cb4666df8ebef380b7bbc8e06538dc501edab5e640e39bdb5b1944567cc76bf

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.640857Z digest=sha256:ecc6d33f42d3a238331f45af8bde79af5e8b6c53bc2df82f545eaec43cdcfd0d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.644875Z digest=sha256:9e839b42aeef9ebed397e564a9f5a5912bda83003d9fbbc2cccee1eb1359469e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.648885Z digest=sha256:0c8146fcb289023813b1f0806074dd8729f9bbea7fd540d3699ea0f00e014cbe

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.652910Z digest=sha256:9e0ac6be0d2d169761c9c9a7118a0234ada7a0386647e2da229495fb8f4d7d0b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.656842Z digest=sha256:a45cefff5478c934e1eab3155d381b2d76627dc46c911f398adec1321392b240

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.660978Z digest=sha256:11fd242b06a31d3e80f60b7d85a95a3fb9b4d23cfb70c8e8c412bdd2a27d6156

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:38:19.485115Z digest=sha256:f98479f47a81cc806ec0591daaa5db54388b3548f673a938d0234ca33bdafdd4

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=sha256:386773ca25cadeef07b3b5f1dd36f83b0662a33b8791d26c8ba5ff8181897ff9

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=sha256:8da0c3b2f61bc94dc2d7c8d118b43ec7e82e711621e63ba57e302a20a2b2aab3

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-09T23:51:47.724033Z digest=sha256:34e5fc5fbb3a504b1f86249bef65ce0cc28713a4c2d8250e3a12872fafc529ab