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Paper Citation Record · LEDGER

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction

As of 18 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:2502.00717.

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

pith.paper-citation-record.v1
2502.00717 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:02:45.221151Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:19:24.774645Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T14:19:25.218317Z

Reference resolution

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy18
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3b22dc06-eb47-44c9-9f03-282b443d89b8 · outbound

This paper cites Qwen Technical Report.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Qwen Technical Report

Reference 1

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unresolved
no resolver link, observed 2026-08-09T18:02:45.050009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.050009Z digest=sha256:e2458d8c27f244122e08949cdaf16823cebde369d5ed4c81cffd2d1e3dc92f70

Observation 343c750e-369e-41c8-9f7d-1aea43af12e6 · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

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unresolved
no resolver link, observed 2026-08-09T18:02:45.055692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.055692Z digest=sha256:6827c99dcc44df336db4c46eaacd1a6d212defb8a8a2fbc74ac5d8b190307ad3

Observation ab325d68-16af-4cea-b535-77d1c8190fff · outbound

This paper cites Y., Bhiwandiwalla, A., Tseng, S.-Y., Olson, M.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Y., Bhiwandiwalla, A., Tseng, S.-Y., Olson, M

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.747062Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.060876Z digest=sha256:8eee706bcee60a919c9df47649b56bee7e6ccdc6a525858ab4f44c8323ed4d87

Observation 9559d8da-160f-4045-9d0a-02a68d05ef0e · outbound

This paper cites Honeybee: Locality-enhanced projector for multimodal llm.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Honeybee: Locality-enhanced projector for multimodal llm

Reference 4

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unresolved
no resolver link, observed 2026-08-09T18:02:45.067233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.067233Z digest=sha256:5a07441e4d15614b260110268d964e79fc417fc11e10b7d917d76895ee08564b

Observation 383ebc9f-4bf6-4de8-bc9d-85bb801cb0f0 · outbound

This paper cites Spatialvlm: Endowing vision-language models with spatial reasoning capabilities.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Spatialvlm: Endowing vision-language models with spatial reasoning capabilities

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.723271Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.072247Z digest=sha256:b2fc8fcf06c3dc41d04a8acc68e25b90cd7533219f60ce525da05b95b26f811f

Observation f88f5eed-8fc8-4fd3-bb2b-bb5685368e1b · outbound

This paper cites An image is worth 1/2 tokens after layer 2: Plug-and-play inference acceleration for large vision-language models.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction An image is worth 1/2 tokens after layer 2: Plug-and-play inference acceleration for large vision-language models

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.708557Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.076964Z digest=sha256:66e012a55dccd1234b50758ab4d58712cc384e6f0a43cdb88616ece463168634

Observation 89cc4221-5b42-401d-86b6-b2dbb14f532e · outbound

This paper cites E., Stoica, I., and Xing, E.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction E., Stoica, I., and Xing, E

Reference 7

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no resolver link, observed 2026-08-09T18:02:45.082246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.082246Z digest=sha256:630aa1cd7da9dceb38b7c44f8390705e0cc82dfead5e86795d072230ff9c53ae

Observation d6157353-10cd-43f9-86e8-79faf796d208 · outbound

This paper cites Vision transformers need registers.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Vision transformers need registers

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.684270Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.086650Z digest=sha256:e5019c75652435c385d17e60025c0ded9b29362d142586e6b9f7649de5d529b6

Observation 5bf0cfb9-7f44-40ca-a3f1-b9f54ccac391 · outbound

This paper cites Intern LM - XC omposer2-4 KHD : A pioneering large vision-language model handling resolutions from 336 pixels to 4k HD.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Intern LM - XC omposer2-4 KHD : A pioneering large vision-language model handling resolutions from 336 pixels to 4k HD

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.670033Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.091136Z digest=sha256:9c45bd1bf223a134edde455505d9487b6728301ddabba01d07781195c97fd0b1

Observation e372e6e3-31ba-4f6a-865b-bc629db98ea6 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

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no resolver link, observed 2026-08-09T18:02:45.095827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.095827Z digest=sha256:b4e0333f22422c949678927dfc5ceba6dea1ce6004e6dfcb92f8d2f7c1273cc5

Observation 2f08a5cf-e9aa-4df2-b351-654abf5b0a14 · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 11

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no resolver link, observed 2026-08-09T18:02:45.100605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.100605Z digest=sha256:17dc08ac6fe29a44d8ec03ab538a4bbe7aebcf1a7efbf4d6ca5cee464a2c7bdb

Observation 95cfe3cb-7e6d-4a2f-baa9-b6167e64caf6 · outbound

This paper cites A., Ma, W.-C., and Krishna, R.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction A., Ma, W.-C., and Krishna, R

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.651387Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.105324Z digest=sha256:af36a73778784b330de956a40ebf2185e2537373bb5a4d5609d760b3f9b5812e

Observation 4ffa2056-e84d-400b-a949-dc8d7f4c3210 · outbound

This paper cites Detecting and preventing hallucinations in large vision language models.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Detecting and preventing hallucinations in large vision language models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.109865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.109865Z digest=sha256:1f437e62a8eaeadd7b896a970e33ac34749e6bfaab375181d2378a3ff160655c

Observation 3a2aeaed-9f09-4a0f-a3b5-70f50e8d4156 · outbound

This paper cites J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.114157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.114157Z digest=sha256:cb756aaf03a2ca1fc86a779cc583a21e5daac71b61f55e0681b5ab837a6afb3d

Observation 30b95d8e-1ec7-475b-afcf-3c95fb442e79 · outbound

This paper cites Lisa: Reasoning segmentation via large language model.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Lisa: Reasoning segmentation via large language model

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.118566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.118566Z digest=sha256:57d969d61a5a17be46d2431e4fb3ad5c65cac68cb3ff711c5f4b05bf032d8303

Observation 349682b0-1ac4-443d-82db-dc44b05e0421 · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Mitigating object hallucinations in large vision-language models through visual contrastive decoding

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.122378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.122378Z digest=sha256:5eb76c6ae5648ab54c096c94fe45c4eb8762f1ee02909e5dbd8de2b3007a1d8e

Observation 64779bfe-e615-4e27-a556-e84bd1fa8e30 · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction L., Holtzman, A., Fried, D., Liang, P., Eisner, J., Hashimoto, T

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.599498Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.126301Z digest=sha256:0fce8c3b8d4b2aef128818f1feb6c5fe446c7760ea76e0be3c95690596287926

Observation f62d742f-848e-496e-880e-a38e7393ee98 · outbound

This paper cites X., and Wen, J.-R.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction X., and Wen, J.-R

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.584380Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.130189Z digest=sha256:d7c53ac1d385de19a188a88ffb4983c923cd15528da5a2bf2c08f792534c778b

Observation 781cc07a-de18-4ce9-95aa-a5efcc45a1b3 · outbound

This paper cites an unresolved cited work.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Unresolved cited work

Reference 19

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unresolved
no resolver link, observed 2026-08-09T18:02:45.134091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.134091Z digest=sha256:724f4eb0f9f25bfa75aaad1f2f3fab7bc58a9fcf18ed8eee202936e7cc8d11c8

Observation 5672227d-54e7-428c-8ba6-7beafcbbd65c · outbound

This paper cites an unresolved cited work.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Unresolved cited work

Reference 20

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unresolved
no resolver link, observed 2026-08-09T18:02:45.138911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.138911Z digest=sha256:73275a38525f5f10d2dd5dd798708a543477cd952b8242295a310471b4747d1d

Observation 571167a3-04f2-4dbf-9284-baab24b883aa · outbound

This paper cites an unresolved cited work.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Unresolved cited work

Reference 21

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unresolved
no resolver link, observed 2026-08-09T18:02:45.142715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.142715Z digest=sha256:3026b389dcbb33dd6062f0034ea7c40f01f39257d311ee2c7746f2e93577fa4b

Observation 97b06fc0-2d68-42f4-b18d-11fab6096eee · outbound

This paper cites an unresolved cited work.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Unresolved cited work

Reference 22

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unresolved
no resolver link, observed 2026-08-09T18:02:45.146514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.146514Z digest=sha256:08b4d155818fe12c5f59f00593fafa3b07213bec96512f022a91619dd8abde83

Observation 0252356e-de8d-423d-9efc-932b5513b6eb · outbound

This paper cites Paying more attention to image: A training-free method for alleviating hallucination in lvlms.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Paying more attention to image: A training-free method for alleviating hallucination in lvlms

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.150444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.150444Z digest=sha256:9928f6ac9f602b7b091de78403c1de74d92c36559ccb79fa7061fbf6c22e831a

Observation 08b1f8ac-079d-4cb0-9e07-ee0e7ba93298 · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.154459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.154459Z digest=sha256:300854a85f4b161dce5b9c3d4391c7fcff85189e1a5f5c0fdea202972b5567ca

Observation ebedfd82-17f5-42e2-aff5-020d954ec983 · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction A., Burns, K., Darrell, T., and Saenko, K

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.514090Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.158411Z digest=sha256:9aa9ccd06d03a3c26af78a1280c1eb039dad1865e2e9e0f2b305114712749605

Observation ce2b2060-7f87-46b3-8445-9512446e5bbb · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction LLaMA: Open and Efficient Foundation Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.162801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.162801Z digest=sha256:9cf6c016bdfdb0caa4a61bcc6cdd9820019d49cb9b0ae912c771cdb95c28c2fd

Observation d0aff9bc-1a78-4a8b-825f-341e3ee67787 · outbound

This paper cites Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.167476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.167476Z digest=sha256:4d1f00d929611ddc98384b025f11273f67ec97b75947c849d5a908b43815b97e

Observation 6329c177-7233-409f-9149-ae22f4970fcc · outbound

This paper cites Dilu: A knowledge-driven approach to autonomous driving with large language models.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Dilu: A knowledge-driven approach to autonomous driving with large language models

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.500108Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.172458Z digest=sha256:d1b367ea1dc4b4837ff63f3a140a4bd48d1e8a802de3068e96205412777d08e4

Observation 369c3dfa-6660-49a0-befb-f956d42bfe32 · outbound

This paper cites Q-instruct: Improving low-level visual abilities for multi-modality foundation models.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Q-instruct: Improving low-level visual abilities for multi-modality foundation models

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.485571Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.176770Z digest=sha256:59da9d9e79c52b055310481ae99795dd4ae89f9b6e3eaa8bc15cc083c44b19a6

Observation cf895cd9-62e4-4ca5-99a7-5fabac22c513 · outbound

This paper cites and Xie, S.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction and Xie, S

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.472927Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.180929Z digest=sha256:34253078afe8a3130b973442670437e62d2a828371955ebdb9ac7827a269dcde

Observation e776ef32-e83d-4066-a204-ccbd657f4f72 · outbound

This paper cites D., and Potts, C.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction D., and Potts, C

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.458914Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.185361Z digest=sha256:43b9b2436467f0748b2eee039f7d9feecae9c7a52d2c165b9c83d32d86af0486

Observation e619e128-cb61-4748-b43d-8ae82552b336 · outbound

This paper cites Efficient streaming language models with attention sinks.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Efficient streaming language models with attention sinks

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.444862Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.189945Z digest=sha256:255d60ccb7e3f3851eb80a4a1969f64991c14a81e43edcfd30c07f5b9a93bdcc

Observation e9bbe534-fe4a-4a91-a9c7-17caf404e538 · outbound

This paper cites Multi-modal concept alignment pre-training for generative medical visual question answering.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Multi-modal concept alignment pre-training for generative medical visual question answering

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.430732Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.194609Z digest=sha256:61ec848eebf0641943d7323fba7e8b20a539034efb898f5c3d95283eb7b218dd

Observation af8a30b9-e676-481c-b2c3-9729c9a16f13 · outbound

This paper cites DeCo: Decoupling Token Compression from Semantic Abstraction in Multimodal Large Language Models.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction DeCo: Decoupling Token Compression from Semantic Abstraction in Multimodal Large Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.199090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.199090Z digest=sha256:6e314d3a576529fe26c9f8cfcafa429b49f1b05466102d9cfbc02acabf715826

Observation eca925e7-d6ec-4a08-a5f2-101acc3a8cdc · outbound

This paper cites Attention prompting on image for large vision-language models.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Attention prompting on image for large vision-language models

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.416106Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.203690Z digest=sha256:f342876374fde435d654b810bc87a84d5c642f08d87a55b091198a555fd1058b

Observation 682319d0-9100-471a-960d-3840f09aa90a · outbound

This paper cites Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.401593Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.208263Z digest=sha256:e739a51d5c987e9f057cea026ebd4268aa09ca21145886097de50b59b1d49923

Observation 6eccde3b-c143-49ff-b44d-ab87ed1cf2ea · outbound

This paper cites Llava-grounding: Grounded visual chat with large multimodal models.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction Llava-grounding: Grounded visual chat with large multimodal models

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:02:45.386299Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-09T18:02:45.212469Z digest=sha256:4c99a69a1eb4c3299528d8bff76473ef371664ede73df6ee6508a983837ffc81

Observation c8558b2e-e214-4e40-ba7c-19c2b880d798 · outbound

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

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.216603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.216603Z digest=sha256:a0be0a3d979435be98a350807e3b85c3be844d01be3aa9c1988ffba1bbed5257

Observation 5cc824b5-e1ea-4247-9981-92659d3c69a5 · outbound

This paper cites write newline.

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction write newline

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-09T18:02:45.221151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:02:45.221151Z digest=sha256:201970dbc5940bbdc4a4cd60e679cd4a8513362704e59e288a4f92c041e69937

Pith citing papers

Observation fd86c048-156a-4a5a-8069-44b7abf78f3a · inbound

Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation cites this paper.

Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T08:14:36.819533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:14:36.819533Z digest=sha256:fd7fd3ccb497858d08c9d50cae38516de0a6271f04b43b763bd49b596ec8964c

Observation c29a50f6-41ab-4ec8-bdbf-1ceed4264b42 · inbound

Test-Time Hallucination Control in Large Vision-Language Models cites this paper.

Test-Time Hallucination Control in Large Vision-Language Models MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction

Reference 52

Resolution
metadata mismatch
local_arxiv, observed 2026-08-15T14:19:25.222689Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-15T14:19:24.774645Z digest=sha256:21d2d052412195df6f48f907f6743a5af9c140a8d8fc2caefdf6a58717fe3332