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Paper Citation Record · LEDGER

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey

As of 7 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 2 inbound Pith citation observations for arXiv:2508.10955.

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

pith.paper-citation-record.v1
2508.10955 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:28:52.191294Z

measured 102 of 102 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T20:27:52.720629Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:18:57.751321Z

Reference resolution

100 of 300 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f2fb718-29bb-4ec3-b487-21245ab8af04 · outbound

This paper cites an unresolved cited work.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Unresolved cited work

Reference 1

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no resolver link, observed 2026-08-05T20:28:41.469013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:28:41.469013Z digest=sha256:01bbd6424981c47ce6f2e3bdc009a2a4f0c48e959bf2151811536f78afd7c5bb

Observation 2258ef16-bc16-47c9-ba82-903bf0a82c93 · outbound

This paper cites GPT-4 Technical Report.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey GPT-4 Technical Report

Reference 2

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no resolver link, observed 2026-08-05T20:28:41.524917Z

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source=arxiv_source observed=2026-08-05T20:28:41.524917Z digest=sha256:c474f1996019595b7c4245bd1e23bfff0d9d0aebe874b79aaa8fa4a176e5ece1

Observation d736a8e6-200f-4293-9f96-61dc05c7a929 · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey LLaMA: Open and Efficient Foundation Language Models

Reference 3

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source=arxiv_source observed=2026-08-05T20:28:41.622512Z digest=sha256:9dfaa79be62ae80247594db6e8ecb9dcc7e616df7ed14c67e8be634d2e101701

Observation e05dd387-78df-4f23-ba43-747e51ab12b8 · outbound

This paper cites Chiang et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Chiang et al

Reference 4

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source=arxiv_source observed=2026-08-05T20:28:41.733277Z digest=sha256:eb4cf38e9a432e03d7e1dc1d15f328eb956450a7915573299842e45e4a50ce6e

Observation 23ede731-bf81-4393-9ade-35fb9f8f3dd3 · outbound

This paper cites Qwen3 Technical Report.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Qwen3 Technical Report

Reference 5

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source=arxiv_source observed=2026-08-05T20:28:41.859213Z digest=sha256:c1692249ffb5becbc828c0fb5027137a47a0130e4189f876adf9439da36a6648

Observation a18470c7-4ca3-499e-99e2-cd8853044bab · outbound

This paper cites DeepSeek-V3 Technical Report.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey DeepSeek-V3 Technical Report

Reference 6

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no resolver link, observed 2026-08-05T20:28:41.951733Z

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source=arxiv_source observed=2026-08-05T20:28:41.951733Z digest=sha256:dea328db81db94dd67fb2819598b66fc84fc341667346155b7e02fa1afbddfed

Observation cab4d624-26b1-4cbb-a585-7dee413ab139 · outbound

This paper cites An et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey An et al

Reference 7

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no resolver link, observed 2026-08-05T20:28:42.024919Z

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source=arxiv_source observed=2026-08-05T20:28:42.024919Z digest=sha256:d6289b9048c37ce329147433a1e6ae28d310b5387a459d84f41804b0e0447488

Observation d61101b5-8340-4d8d-aa84-089910337da4 · outbound

This paper cites Kasneci et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Kasneci et al

Reference 8

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no resolver link, observed 2026-08-05T20:28:42.144398Z

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source=arxiv_source observed=2026-08-05T20:28:42.144398Z digest=sha256:8a2ac5bc3410b1bc3d5e33f9c036f32b097d63ff47e710aa3f6c1a5814e8edb4

Observation 64ebf1ea-761c-4911-b705-e61c630d1ac9 · outbound

This paper cites Knowledge Acquisition Disentanglement for Knowledge-based Visual Question Answering with Large Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Knowledge Acquisition Disentanglement for Knowledge-based Visual Question Answering with Large Language Models

Reference 9

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source=arxiv_source observed=2026-08-05T20:28:42.220021Z digest=sha256:4b6f1c7cd223163e063126ac8b1dacd7cb3011d989fbb8121a62e87a235b3197

Observation 07239a44-8713-4a3b-bcb2-c2b3efcf6a0a · outbound

This paper cites M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning

Reference 10

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source=arxiv_source observed=2026-08-05T20:28:42.331519Z digest=sha256:5f87132c8d452cbf8ec84104d4a5b77ad0f7d53debeee3b64a1aee8e3d4e0c5a

Observation b473df2b-26fa-45c2-af03-c07c9c9342e8 · outbound

This paper cites Visual Instruction Tuning.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Visual Instruction Tuning

Reference 11

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source=arxiv_source observed=2026-08-05T20:28:42.443220Z digest=sha256:bf215c7f7b217e0e8c92f77004574810d2ac13d01d993cfe3bcee955648eba23

Observation 1fdd6650-5428-4396-8f64-9fbeec244fe3 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 12

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source=arxiv_source observed=2026-08-05T20:28:42.563682Z digest=sha256:36e52b0370e2d4975e818e2738953339879d04ff57fa22fbddd25c81a1a0431b

Observation b06de1ac-c9e3-4293-9dab-05b0b7c930af · outbound

This paper cites Qwen2.5-VL Technical Report.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Qwen2.5-VL Technical Report

Reference 13

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no resolver link, observed 2026-08-05T20:28:42.618365Z

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source=arxiv_source observed=2026-08-05T20:28:42.618365Z digest=sha256:fa067ec5b9fd52093da1564876d0e98eea9f689545b829f063f38b7dbf2aea8f

Observation 4962fb21-1c3a-41e3-b514-7ea6a905f0b7 · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 14

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source=arxiv_source observed=2026-08-05T20:28:42.697303Z digest=sha256:0ebddd4fd4de80381e9af57a8f615ab378676d160fd2a48ba420cebc91beac30

Observation c7a4a81f-d2b0-4048-b439-29b51b25a810 · outbound

This paper cites Yin et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Yin et al

Reference 15

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no resolver link, observed 2026-08-05T20:28:42.760493Z

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source=arxiv_source observed=2026-08-05T20:28:42.760493Z digest=sha256:6ab9dd4e1a02aec5851938e7a4a2c836cfb7135fa95a7ced481449ee12f5c0cc

Observation 34d56379-a8db-48d8-a329-5bc2da962a82 · outbound

This paper cites Lin et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Lin et al

Reference 16

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source=arxiv_source observed=2026-08-05T20:28:42.847520Z digest=sha256:7c328ff69fdb01767bdf32d35df5e26cdf34a54906614f74b6e8fdcd419ea94e

Observation a9665dd2-907f-4382-b649-b6ff4213d51a · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Hallucination of Multimodal Large Language Models: A Survey

Reference 17

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no resolver link, observed 2026-08-05T20:28:42.950551Z

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source=arxiv_source observed=2026-08-05T20:28:42.950551Z digest=sha256:73700008f15ff54f00539c08a6077389f410f410b7a3dd29af1c7ebaad28ab14

Observation 22d35c98-0622-4d60-bdf2-b5789a6d4b28 · outbound

This paper cites Zhang et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Zhang et al

Reference 18

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no resolver link, observed 2026-08-05T20:28:43.042012Z

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source=arxiv_source observed=2026-08-05T20:28:43.042012Z digest=sha256:c4b3e7ed9645f80772c23337239a4f9c86a084889c4aa8147da0f313efd31487

Observation 12856245-0a20-44c8-8ffa-7049acf5904e · outbound

This paper cites A Review of Multimodal Explainable Artificial Intelligence: Past, Present and Future.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey A Review of Multimodal Explainable Artificial Intelligence: Past, Present and Future

Reference 19

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source=arxiv_source observed=2026-08-05T20:28:43.121644Z digest=sha256:8fae6b42d4ae3fa62c5a8b47cbc8f198f362ce073f38cda54b72e5ebd23a5cd3

Observation d3aa965b-2c8f-4d9d-8d30-5ca10b9abcad · outbound

This paper cites Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey

Reference 20

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no resolver link, observed 2026-08-05T20:28:43.224757Z

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source=arxiv_source observed=2026-08-05T20:28:43.224757Z digest=sha256:d75ee9dac19d1dbdc4abd72f469b2cb79858d30d2b3f2f0059bfe84b73f4d357

Observation fd7a79f2-1d69-4e3e-964b-b976d4b4fd4d · outbound

This paper cites Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT

Reference 21

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no resolver link, observed 2026-08-05T20:28:43.326276Z

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source=arxiv_source observed=2026-08-05T20:28:43.326276Z digest=sha256:f6dde7c464c28242b295ad867636c8fd29cededba945710dda795b42eb9d9500

Observation 2c97d7f4-7208-4a69-bd79-d5e52ea82be5 · outbound

This paper cites Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving

Reference 22

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no resolver link, observed 2026-08-05T20:28:43.426121Z

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source=arxiv_source observed=2026-08-05T20:28:43.426121Z digest=sha256:414f869213ef49bfb043d40035521af7077e9e9db548dd06ac0adfff8e252bbb

Observation c769756a-00d4-4e3d-b21b-eeb99253c3fa · outbound

This paper cites GPT-4o System Card.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey GPT-4o System Card

Reference 23

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no resolver link, observed 2026-08-05T20:28:43.492381Z

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source=arxiv_source observed=2026-08-05T20:28:43.492381Z digest=sha256:c308f66d184dfbe7160ed90750c6be825f764b423addc389fd02890efeb66f54

Observation 2cf41a9d-2598-469b-9396-77c7ece97dca · outbound

This paper cites Radford et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Radford et al

Reference 24

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no resolver link, observed 2026-08-05T20:28:43.533627Z

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source=arxiv_source observed=2026-08-05T20:28:43.533627Z digest=sha256:c99c966c091e13079947f1b56ef5db705a93a3fbde9543c17a48a874259d7cf8

Observation 3485b36e-c28b-45d9-8a9d-807f7c7776ac · outbound

This paper cites Liu et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Liu et al

Reference 25

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source=arxiv_source observed=2026-08-05T20:28:43.606912Z digest=sha256:b3266cf9860006800ef7ef4a185c1c99100cbbac20a50c4bd420643eee7feaea

Observation 02a08343-6cf2-43bf-89e7-97f13a1bbb51 · outbound

This paper cites Elizalde et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Elizalde et al

Reference 26

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source=arxiv_source observed=2026-08-05T20:28:43.727323Z digest=sha256:a799657586ec8e2161065c742faea19fa62c7765ef077f6fdaa5aec97856e18c

Observation 64e5f3c9-5f95-4f88-965a-c6183ce17177 · outbound

This paper cites What matters when building vision-language models?.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey What matters when building vision-language models?

Reference 27

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source=arxiv_source observed=2026-08-05T20:28:43.838854Z digest=sha256:d6b47a0e56222f2ca638cf0d9a8e3613395b460d96bc884a4d976330551dd72b

Observation a4e7c2ad-81d5-4c42-b8bf-7c5703b7ca60 · outbound

This paper cites Qwen Technical Report.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Qwen Technical Report

Reference 28

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source=arxiv_source observed=2026-08-05T20:28:43.983832Z digest=sha256:412a6e4926c2b0433f50e035d002607adb43ddf99ea00f25a42a9463e29db3e2

Observation afead839-0fb5-4305-9154-7fc022883982 · outbound

This paper cites Qin et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Qin et al

Reference 29

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no resolver link, observed 2026-08-05T20:28:44.124510Z

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source=arxiv_source observed=2026-08-05T20:28:44.124510Z digest=sha256:19f05535ced3ef0fb950def6b31e195b8119f05d52003ccc28373cd5c87bf144

Observation 57aad9ac-02b3-43f9-add2-5a200a07c74d · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 30

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source=arxiv_source observed=2026-08-05T20:28:44.315363Z digest=sha256:9c1de4bdf83566fae4bde80de2f79bf9fa2b62c004bd19793df243068760ed6b

Observation 22d363ff-ec68-4982-b136-9c4ba7dffbba · outbound

This paper cites Visual Hallucinations of Multi-modal Large Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Visual Hallucinations of Multi-modal Large Language Models

Reference 31

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no resolver link, observed 2026-08-05T20:28:44.432144Z

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source=arxiv_source observed=2026-08-05T20:28:44.432144Z digest=sha256:0ff2ecf4ae586ba1b325d2bc641ea8650ef4120c2afd73002282089105600117

Observation c12a7cc3-1498-4452-9ffc-fa7f5886e854 · outbound

This paper cites The Instinctive Bias: Spurious Images lead to Illusion in MLLMs.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey The Instinctive Bias: Spurious Images lead to Illusion in MLLMs

Reference 32

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source=arxiv_source observed=2026-08-05T20:28:44.587330Z digest=sha256:142c807cdedc88c4985ed484468713f62878b6befa6971a4fdc5632243a41485

Observation 9d40d457-af28-43b3-be63-4463d4b14ac5 · outbound

This paper cites Tong et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Tong et al

Reference 33

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source=arxiv_source observed=2026-08-05T20:28:44.741597Z digest=sha256:4d5e8fa68a4976aca30034af99b8140eab1167bacd6409f2452a51d09f5b7717

Observation 318cb45d-effe-41c7-b7e0-09a9ce057d9f · outbound

This paper cites Sharma et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Sharma et al

Reference 34

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source=arxiv_source observed=2026-08-05T20:28:44.881114Z digest=sha256:b23b33e2ef345aaecc87359b80d03f6c17029f1ae3abe8f9f762cfe0700ffae2

Observation b3bbfc0d-aab2-4e88-b0ab-1ef73dd05fb4 · outbound

This paper cites Chambers et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Chambers et al

Reference 35

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source=arxiv_source observed=2026-08-05T20:28:45.069393Z digest=sha256:26872a866a6dbd1768303d2356b8138bb86042bc6e559fe57177b0eb6fe739f8

Observation 4cb69058-bd2c-462f-ae8f-ff6dbf3a4435 · outbound

This paper cites PaLI: A Jointly-Scaled Multilingual Language-Image Model.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey PaLI: A Jointly-Scaled Multilingual Language-Image Model

Reference 36

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no resolver link, observed 2026-08-05T20:28:45.232824Z

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source=arxiv_source observed=2026-08-05T20:28:45.232824Z digest=sha256:c15abc9bb16fb8346390b3d170ed840b0f35dc80479e2a135e371baf7dee9ced

Observation 3b0f3e3a-84a1-428e-ac05-6cf7511bc3f0 · outbound

This paper cites Schuhmann et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Schuhmann et al

Reference 37

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source=arxiv_source observed=2026-08-05T20:28:45.432745Z digest=sha256:0bc857094753e3b8ab75d18d0abb39c0c0625a4f83fa719bb5d743993d373652

Observation 9d71db80-9ebd-4a82-b353-7d4a0bfa00dc · outbound

This paper cites an unresolved cited work.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Unresolved cited work

Reference 38

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source=arxiv_source observed=2026-08-05T20:28:45.563613Z digest=sha256:989341a6103bae4811795a837cb5a4105c3318e43daeff74e6333edbbbcf0530

Observation 2b99854b-a477-4bb7-bd01-21913631e7b5 · outbound

This paper cites Jia et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Jia et al

Reference 39

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source=arxiv_source observed=2026-08-05T20:28:45.781618Z digest=sha256:9a5976db18ff32b9195d4d7031eeb34a86b0208300b621807c5f5d43e7f37e92

Observation e71ed163-06ac-4b63-8c53-65a3a1e9aa55 · outbound

This paper cites Zhu et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Zhu et al

Reference 40

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source=arxiv_source observed=2026-08-05T20:28:45.913294Z digest=sha256:8fe65cd1a116e44ba8b599ace60f7014e8b73c823e2857affe0391af1af9f0c7

Observation e0668e98-25d4-47a8-8736-4fde5a611fd5 · outbound

This paper cites Gu et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Gu et al

Reference 41

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source=arxiv_source observed=2026-08-05T20:28:46.009183Z digest=sha256:5063d1bc34d8ff2fad86c10c51722e1065228afa51eb0da3681c0d1874ab60d8

Observation 2a252014-c327-4978-a936-d376047e8ef3 · outbound

This paper cites Srinivasan et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Srinivasan et al

Reference 42

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source=arxiv_source observed=2026-08-05T20:28:46.142635Z digest=sha256:d5df2898d6afb67d48051b92e0d8d7141ad108a763549ef60b0ebb055f838fca

Observation 283d106f-4e62-45b8-97bb-031c1ddea906 · outbound

This paper cites Changpinyo et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Changpinyo et al

Reference 43

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source=arxiv_source observed=2026-08-05T20:28:46.271710Z digest=sha256:288d0d99df3c0f05d4d2754afdb3a0c031aeb3f864aae54bdc7512965c4b3ea3

Observation 147de0dc-a5af-442c-8652-8b7cca3e7869 · outbound

This paper cites RedCaps: web-curated image-text data created by the people, for the people.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey RedCaps: web-curated image-text data created by the people, for the people

Reference 44

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source=arxiv_source observed=2026-08-05T20:28:46.376809Z digest=sha256:51d32b17092b373cd400f35250f934e8c9c3d5966cbfd272300f176dcc9d9e64

Observation 7da3b7e4-3912-42b7-8476-7b73c77741b9 · outbound

This paper cites Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models

Reference 45

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source=arxiv_source observed=2026-08-05T20:28:46.452098Z digest=sha256:f59a12f50977a3a2bbd4d4fd100fc531e953695ee2c36977587e5d7a74625e30

Observation 9df81e88-3a55-4182-ba61-e09d4f32fdda · outbound

This paper cites Goyal et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Goyal et al

Reference 46

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source=arxiv_source observed=2026-08-05T20:28:46.559439Z digest=sha256:4dfea7fa2f9cf9091131418ca0da846d7c8098dbe7666d3b9af9bbaf3ca277b9

Observation 51043a50-dae6-44d3-88ac-8b139f157df7 · outbound

This paper cites AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding

Reference 47

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source=arxiv_source observed=2026-08-05T20:28:46.686307Z digest=sha256:41fcd5f2439446120acfa9000685c09f119117358b32f25f526b39e306bc518a

Observation fbd3b915-91b4-4521-bd45-70973a5ae995 · outbound

This paper cites Ordonez et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Ordonez et al

Reference 48

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source=arxiv_source observed=2026-08-05T20:28:46.810039Z digest=sha256:ccfae68b6ce8ba044a4efbb8d8a352449b45f5cec178e8947bf10be28a303813

Observation e6bc4879-1119-44c8-a419-931966662dcb · outbound

This paper cites LongHalQA: Long-Context Hallucination Evaluation for MultiModal Large Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey LongHalQA: Long-Context Hallucination Evaluation for MultiModal Large Language Models

Reference 49

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source=arxiv_source observed=2026-08-05T20:28:46.884757Z digest=sha256:82453fcf520e0d3e294a6278d33f85236b0a1146ac6b9dcadb1d1e181add272b

Observation ba96c738-9179-45e6-aab5-624306115f80 · outbound

This paper cites AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 50

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source=arxiv_source observed=2026-08-05T20:28:47.015807Z digest=sha256:48c5eb12e81aee8bf7bb1094d0fbc89e4c267d0f7c030cc8d6e52cc383b9a4dc

Observation b35ac00b-b915-4d25-bdd9-1b6bcf41f0d4 · outbound

This paper cites Kaul et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Kaul et al

Reference 51

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source=arxiv_source observed=2026-08-05T20:28:47.128579Z digest=sha256:0a7da50c888f0ad70573b78291617ad1857cba3e33de3bb4da69659af3f7fe89

Observation 0bf22715-974b-4794-8525-c081ffe87aa6 · outbound

This paper cites PhD: A ChatGPT-Prompted Visual hallucination Evaluation Dataset.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey PhD: A ChatGPT-Prompted Visual hallucination Evaluation Dataset

Reference 52

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source=arxiv_source observed=2026-08-05T20:28:47.282413Z digest=sha256:d4036386beb3910ba89347d5497b8f172d259064559998c12f244255470249b1

Observation f4f25f46-fc6d-4fa4-9a9d-e03bd9b1fa22 · outbound

This paper cites Gao et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Gao et al

Reference 53

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source=arxiv_source observed=2026-08-05T20:28:47.442410Z digest=sha256:7025e629b66341b9c14e906b9b3393e4e10f81dcb5c48adcc56d910f154ae3d1

Observation cd753afd-ec0b-4db6-ad30-ce52cf740ecd · outbound

This paper cites How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts

Reference 54

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source=arxiv_source observed=2026-08-05T20:28:47.627486Z digest=sha256:8c381ac7367e5e9273ccdff5ac9cbe7e72a213a4811415b7547a2cdad7298306

Observation c6e8bad8-9633-477a-ad0b-7a306ceedcf0 · outbound

This paper cites Mitigating Open-Vocabulary Caption Hallucinations.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Mitigating Open-Vocabulary Caption Hallucinations

Reference 55

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source=arxiv_source observed=2026-08-05T20:28:47.779619Z digest=sha256:2894a97260c53aef35034d54a14e0190cfc1131b67a23eed28c78316a63dd633

Observation 23e1a9fc-e9b4-4f96-bf7a-2ba4b7e66968 · outbound

This paper cites Wang et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Wang et al

Reference 56

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source=arxiv_source observed=2026-08-05T20:28:47.865301Z digest=sha256:5405721fcc1a54bf4c21e3710b830a525cc39d7ef9aaaa910ce40d9fe78f51b1

Observation 98871d96-177c-4b34-85fe-4b2b3af39ab6 · outbound

This paper cites Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models

Reference 57

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source=arxiv_source observed=2026-08-05T20:28:47.982948Z digest=sha256:902566566a28f7a83d39ed8c41346936193028a15c394bd824d4dd69a6e77ec2

Observation f7ecc5b3-94a7-4931-a6f4-af7df11838e5 · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 58

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source=arxiv_source observed=2026-08-05T20:28:48.136224Z digest=sha256:66da3395016cc7973a3aabd4d985271d05bf0fc71499e6e3270b95b6af4fb3d6

Observation acd2758d-9be4-4bea-959a-d49958327050 · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey CIEM: Contrastive Instruction Evaluation Method for Better Instruction Tuning

Reference 59

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source=arxiv_source observed=2026-08-05T20:28:48.314931Z digest=sha256:00f1ca86d664390a60f2fde75efd80d9972e3d3c519172830cdd1eb31815c296

Observation 8008bae5-a180-48ea-aea7-188653c24258 · outbound

This paper cites Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models

Reference 60

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source=arxiv_source observed=2026-08-05T20:28:48.416727Z digest=sha256:d2ecd3554a84699be6bb349cbb4e16693f6869cdb2c866bdd2bc0c533de9a19a

Observation da879e89-1fa4-4893-b6cd-b2135a2a2a45 · outbound

This paper cites Silkie: Preference Distillation for Large Visual Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Silkie: Preference Distillation for Large Visual Language Models

Reference 61

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source=arxiv_source observed=2026-08-05T20:28:48.508649Z digest=sha256:4b818618990a8b5ee825c7e9bb8cee612105d6197b3e8c65cbc256ef0ad07c23

Observation 24ee279a-d617-4c2e-8ef1-207577892b19 · outbound

This paper cites Kafle et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Kafle et al

Reference 62

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source=arxiv_source observed=2026-08-05T20:28:48.623443Z digest=sha256:9c96efcff1c945fdfa74e7295abb3a7f4a5904c9441cc40b50c6e1850f928fc5

Observation 0ea56995-7318-4e76-8dfe-129bd3d1cb6e · outbound

This paper cites Nie et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Nie et al

Reference 63

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source=arxiv_source observed=2026-08-05T20:28:48.714821Z digest=sha256:7aca7005929f08b7a98f7baa5d57d2b760699b85b9db1f530c24bad17f6b61d7

Observation aca49152-8d3b-419e-b935-04d214d8905d · outbound

This paper cites Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models

Reference 64

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source=arxiv_source observed=2026-08-05T20:28:48.783895Z digest=sha256:5edcb42ad8ed9917f113f57c76b8493f6d3ea53d4cd0e61b83c175fa9ae18b85

Observation 770d11c5-79f1-426e-bb62-9151f70f6809 · outbound

This paper cites Ziyang et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Ziyang et al

Reference 65

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source=arxiv_source observed=2026-08-05T20:28:48.890772Z digest=sha256:df809b575755346c6d80cc5640cde38f88ffe0e3eadaebcfd19235a42a4b1197

Observation 088d517e-e909-44ef-895b-f1ffda52cd07 · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey ALOHa: A New Measure for Hallucination in Captioning Models

Reference 66

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source=arxiv_source observed=2026-08-05T20:28:48.983205Z digest=sha256:5ceb4fb95e6ac2195a1e14a96c275bef0e493192ca043a628c456397cb767f50

Observation 913e0e28-253a-4fda-b448-05d31844867b · outbound

This paper cites Jiang et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Jiang et al

Reference 67

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source=arxiv_source observed=2026-08-05T20:28:49.059448Z digest=sha256:ebd3450e3c4617dd7ba1cba8d9f474e9a59fbee2bbaa6402457ed2bcc057c236

Observation 14cf1ee1-3e11-41fa-a9f3-b8b7142b50d3 · outbound

This paper cites Unified Hallucination Detection for Multimodal Large Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Unified Hallucination Detection for Multimodal Large Language Models

Reference 68

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source=arxiv_source observed=2026-08-05T20:28:49.194785Z digest=sha256:b45688794f9af7855a749aceb00cc14a77292424711d9743fea110665152fb35

Observation c1b8dbde-b7c6-45be-b805-c4e16b767442 · outbound

This paper cites Villa et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Villa et al

Reference 69

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source=arxiv_source observed=2026-08-05T20:28:49.259291Z digest=sha256:2d8985d7f2bd052d5b70632d24470dd98271989c88290c4acafd3b4244a6369c

Observation 47ddd280-18d3-4e45-805d-1302506791bd · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Mitigating Hallucination in Visual Language Models with Visual Supervision

Reference 70

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source=arxiv_source observed=2026-08-05T20:28:49.334319Z digest=sha256:5aa8b92f59751bf8023403b2fd5dd71bf322daa992ee54fe4dd2419eb335b7dd

Observation 2b871298-39fa-489e-bb07-c819cefd682e · outbound

This paper cites HallE-Control: Controlling Object Hallucination in Large Multimodal Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey HallE-Control: Controlling Object Hallucination in Large Multimodal Models

Reference 71

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source=arxiv_source observed=2026-08-05T20:28:49.437336Z digest=sha256:a04910297f49e1686ea0c38b28af8c8bedd4c5aed2914842d24f05740fc69b16

Observation 81dd63a9-3c10-496d-8a39-9ecb23b1185a · outbound

This paper cites Evaluation and Analysis of Hallucination in Large Vision-Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Evaluation and Analysis of Hallucination in Large Vision-Language Models

Reference 72

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source=arxiv_source observed=2026-08-05T20:28:49.541282Z digest=sha256:3dd53063298bf4e1571e0389254abaad85acfa583c76c6f93077cbc2529bc584

Observation 26eec382-7c9a-4d06-a3bf-535d40461e6e · outbound

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

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Evaluating Object Hallucination in Large Vision-Language Models

Reference 73

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source=arxiv_source observed=2026-08-05T20:28:49.638187Z digest=sha256:5de67c1d44cdf473e29b58553fd0a7607031fde067de6256be9bbce749e51f3c

Observation bcf651fa-8d24-4cab-a038-bd692a4e5221 · outbound

This paper cites List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs

Reference 74

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source=arxiv_source observed=2026-08-05T20:28:49.694202Z digest=sha256:0088d8b2027d746dfdd0f476272cfae3e4a4bfd977a2e6b785147e1bd818b391

Observation 10f44f90-3439-48c5-a627-fdb6bc2b3b8a · outbound

This paper cites Gunjal et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Gunjal et al

Reference 75

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source=arxiv_source observed=2026-08-05T20:28:49.826237Z digest=sha256:7058e4229190a5c9205d24bf16a7889e10cf1ab1ddf68177af3b7f7e150ab82c

Observation 6a4e3b08-9a8d-47ce-ad5c-02988886fb15 · outbound

This paper cites Towards a Systematic Evaluation of Hallucinations in Large-Vision Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Towards a Systematic Evaluation of Hallucinations in Large-Vision Language Models

Reference 76

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source=arxiv_source observed=2026-08-05T20:28:49.900662Z digest=sha256:d9ccea2acfe243cdd9465bb487df5498717f37d899938cf10b93f67b1f8e6181

Observation 67395221-9853-4575-b4c2-3f03ae334068 · outbound

This paper cites VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models

Reference 77

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source=arxiv_source observed=2026-08-05T20:28:49.973347Z digest=sha256:cbe508af34dc83d3c3e27951220490da55d004af0866aa8f9a0d3065bcd33174

Observation 4e7533f3-45be-49f4-8ab8-417bdd1a5967 · outbound

This paper cites IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models

Reference 78

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source=arxiv_source observed=2026-08-05T20:28:50.070895Z digest=sha256:7843f851eeae0af1c7110ce590c21bbe13bdc315c5000c23ab749887e39e711f

Observation cdde58e5-e4a9-4195-b617-8df115b4e787 · outbound

This paper cites Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs

Reference 79

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source=arxiv_source observed=2026-08-05T20:28:50.178489Z digest=sha256:e79f509eb16a0d0915cfd6642aa3db03537c7708a4a7cb6c44e85a4eeb738f86

Observation 8f36471a-4472-4aa5-ad8c-c338ceb54975 · outbound

This paper cites Li et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Li et al

Reference 80

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source=arxiv_source observed=2026-08-05T20:28:50.335758Z digest=sha256:2bf4bb0081031a59086ab750d58f2afd410097367f20f2de97e54fdd49d29d52

Observation adcd05e1-380d-4541-98a8-311c49b126b6 · outbound

This paper cites Byeon et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Byeon et al

Reference 81

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source=arxiv_source observed=2026-08-05T20:28:50.471161Z digest=sha256:c273a98daec6abb4731c8f24899c56e2913039bd51e76bd0f6b5372a2b5b4d9a

Observation 840da11f-dd03-4f2c-a372-f4f35cca9a3e · outbound

This paper cites Lauren c on et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Lauren c on et al

Reference 82

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source=arxiv_source observed=2026-08-05T20:28:50.566935Z digest=sha256:72daaa52098ce5a9f14435059dfb8e61e03ba01ea3de74528e883ab09a87c7bd

Observation 40c2c92c-2c1b-4cfb-93a9-05f9952b7e04 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey DINOv2: Learning Robust Visual Features without Supervision

Reference 83

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source=arxiv_source observed=2026-08-05T20:28:50.643441Z digest=sha256:4f6cf0fa5ec8fd72e8736aa318ee6e62306fe59eea91ddabec99cbfbde7083c7

Observation 9d137212-55cc-45c6-9f4a-ddb0a7fbece3 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 84

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source=arxiv_source observed=2026-08-05T20:28:50.768814Z digest=sha256:e177ddd81fa902ce88d95b980b91877c926ddf46f07d997f44b7e8d9d0695992

Observation 05d19ee4-74cf-440e-9db5-892c5d424c3e · outbound

This paper cites Betker et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Betker et al

Reference 85

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source=arxiv_source observed=2026-08-05T20:28:50.899877Z digest=sha256:a6149a95ec66f5d674202b7fd58629cafe227441838d3f98557567dd7be8341e

Observation 0b5a4440-8300-4fe0-b41c-010f3c933b20 · outbound

This paper cites Zou et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Zou et al

Reference 86

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source=arxiv_source observed=2026-08-05T20:28:51.006079Z digest=sha256:4aafc57584a7cb2d4e60c4af7efb29b93e3fd81421ea9d677229fdcc1d118ac6

Observation 93f97d2d-4b46-4897-8b7f-6629373d4f03 · outbound

This paper cites Liu et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Liu et al

Reference 87

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source=arxiv_source observed=2026-08-05T20:28:51.106784Z digest=sha256:c870386b6ffeed0d0b3d07e2c792101cbb52e1c1f94c722e38f24bfab1a3ae8f

Observation b40bbb30-3b13-4ef7-8848-2f6f9b4f1bcb · outbound

This paper cites Open-Set Image Tagging with Multi-Grained Text Supervision.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Open-Set Image Tagging with Multi-Grained Text Supervision

Reference 88

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source=arxiv_source observed=2026-08-05T20:28:51.187504Z digest=sha256:89e25840dac009f5d60403fee1f89e1e5ea5c7eb961b6a4d566cc62f48212f9e

Observation 4e4c4c8c-4eb8-428b-80ff-01afa466fc88 · outbound

This paper cites Li et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Li et al

Reference 89

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source=arxiv_source observed=2026-08-05T20:28:51.297123Z digest=sha256:7f164137b1997e9d609757ac30d1ed2ad6c107563a8120c1d0ed09b733a71f92

Observation 2cf69c53-d2e1-44e5-80f6-76e4799599e8 · outbound

This paper cites GME: Improving Universal Multimodal Retrieval by Multimodal LLMs.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Reference 90

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source=arxiv_source observed=2026-08-05T20:28:51.375646Z digest=sha256:eec827c004c229a2eef917bee59fb0344b0e4b377871dd8967c8eab16d456b9a

Observation 767ec9f3-ae42-44a9-aeab-83b655885d65 · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 91

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source=arxiv_source observed=2026-08-05T20:28:51.467961Z digest=sha256:caceafce4e6c73c7e6d1ad780f5c94f044e036eb469052399f843dbfbbb3140a

Observation b431ca53-5024-465e-9b2d-c736f5dc472f · outbound

This paper cites Saito et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Saito et al

Reference 92

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source=arxiv_source observed=2026-08-05T20:28:51.557669Z digest=sha256:c85ca1661bea6c13915ada788355f10bfe6b6c790f72ecde073d17a390c29edd

Observation be3ee836-3f7e-4fd2-971d-d00cfd9c9411 · outbound

This paper cites XL-HeadTags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tags.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey XL-HeadTags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tags

Reference 93

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source=arxiv_source observed=2026-08-05T20:28:51.655385Z digest=sha256:c168340074795ed5a1ad7af68701ff92bbf7d1a971abfe6f3e141cee6f642216

Observation f7871e68-32ff-4d91-81aa-d9d2307a3a28 · outbound

This paper cites EchoSight: Advancing Visual-Language Models with Wiki Knowledge.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey EchoSight: Advancing Visual-Language Models with Wiki Knowledge

Reference 94

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source=arxiv_source observed=2026-08-05T20:28:51.739526Z digest=sha256:7d27989042dc0693e3e8d32f8e52c7ae79f26b0484501f1feb3158f11ef76e7f

Observation 4b149840-36e3-4d13-b735-cfdd2c01c29f · outbound

This paper cites Kumar and P.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Kumar and P

Reference 95

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source=arxiv_source observed=2026-08-05T20:28:51.800324Z digest=sha256:c23fd3e74cbc24844f76deaf076a3c9f3bcd6fc9b05a995fe91dda77a1e0ce98

Observation 9235856d-cb35-4fec-8c01-e346cd6034cb · outbound

This paper cites VISA: Retrieval Augmented Generation with Visual Source Attribution.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey VISA: Retrieval Augmented Generation with Visual Source Attribution

Reference 96

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source=arxiv_source observed=2026-08-05T20:28:51.876984Z digest=sha256:cbc826d6ab5e277489287a23935ffd8b114d0882033058a1677a182357321be5

Observation 2f9a4ea2-6a6e-47df-b9ff-e16ec39b4af8 · outbound

This paper cites Ren et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Ren et al

Reference 97

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source=arxiv_source observed=2026-08-05T20:28:51.969062Z digest=sha256:77dfe6221f6c5d8c406f91b552c04747074c859813622d5302f157512ec29450

Observation 08ce3dca-bdba-4435-9668-3dd3dae8d9be · outbound

This paper cites Ma et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Ma et al

Reference 98

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source=arxiv_source observed=2026-08-05T20:28:52.041893Z digest=sha256:ad40cfd2515e4bbd28d9e6a0eb13998a0c54bbef4993a88ab5827150a209c60a

Observation f8a7af74-cb65-4375-9201-c75d62c4d36a · outbound

This paper cites Shen et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Shen et al

Reference 99

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source=arxiv_source observed=2026-08-05T20:28:52.116884Z digest=sha256:d719326ab4a3d04bb13a89aeb273515b98325cff9ee9652ccd8042f324edbd9b

Observation 8fe96440-6c2e-44e5-aa81-47ee63b4737a · outbound

This paper cites Zhang et al.

Empowering Multimodal LLMs with External Tools: A Comprehensive Survey Zhang et al

Reference 100

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source=arxiv_source observed=2026-08-05T20:28:52.191294Z digest=sha256:141545a945d4268e4be1979f98d99af75a204c7ca098c9d25cbac91f83bd5d23

Pith citing papers

Observation 66da2b2f-aac1-4605-85ed-e3100fe7ca98 · inbound

Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMs cites this paper.

Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMs Empowering Multimodal LLMs with External Tools: A Comprehensive Survey

Reference 1

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arxiv_id, observed 2026-06-30T20:35:02.890082Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T20:27:52.720629Z digest=sha256:c27e7aec7b5979b75ff02e196cb07c9a6d41c569b785834e55fb897152835d1b

Observation b8975de9-c192-4cd4-98ae-63ccf5f60752 · inbound

MathVis-Fine: Aligning Visual Supervision with Necessity via Progressive Dependency-Guided Training for Multimodal Mathematical Reasoning cites this paper.

MathVis-Fine: Aligning Visual Supervision with Necessity via Progressive Dependency-Guided Training for Multimodal Mathematical Reasoning Empowering Multimodal LLMs with External Tools: A Comprehensive Survey

Reference 112

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arxiv_id, observed 2026-07-03T20:18:57.753169Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T01:23:40.564561Z digest=sha256:c55f56088dceb0b199fd83bbfd61901dc1db9429c48e4a6235be0a890f63e35f