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Paper Citation Record · LEDGER

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories

As of 5 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2602.10809.

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

pith.paper-citation-record.v1
2602.10809 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T01:02:35.739213Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved39
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e703c280-ad41-4414-b796-56356ad3d700 · outbound

This paper cites Introducing claude opus 4.5, 2025 a.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Introducing claude opus 4.5, 2025 a

Reference 1

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source=arxiv_source observed=2026-08-03T01:02:32.481330Z digest=sha256:1b209a158ac9f8ffc010580b68bccc8e7adbef33d45b89e1c7986428bed5bdeb

Observation 0c3cd124-f102-4b22-b40c-74306fe7aab0 · outbound

This paper cites Introducing claude sonnet 4.5, 2025 b.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Introducing claude sonnet 4.5, 2025 b

Reference 2

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source=arxiv_source observed=2026-08-03T01:02:32.519876Z digest=sha256:0f8368d0be672ab038fb4aab8d1fee58bea1e2e6408f90cb68070dafd8ed42ce

Observation b349e52a-5994-4ac3-97de-6beed00b7849 · outbound

This paper cites Qwen3-VL Technical Report.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Qwen3-VL Technical Report

Reference 3

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source=arxiv_source observed=2026-08-03T01:02:32.574737Z digest=sha256:70417c438d0fffa1a9dc223cc525643d09021cb52199997722c88883739616c3

Observation 6e93fd0d-42b5-4259-bd2b-04f63bc3beaf · outbound

This paper cites Seed1.6-embedding.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Seed1.6-embedding

Reference 4

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source=arxiv_source observed=2026-08-03T01:02:32.635539Z digest=sha256:68e93bcb655b60bbf2acc6333451c1ecd550bd00bd858c208204fdfd442b47b1

Observation 12d175b6-6b6f-42b9-9584-86eab0bb3b58 · outbound

This paper cites MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings

Reference 5

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source=arxiv_source observed=2026-08-03T01:02:32.688658Z digest=sha256:4029b174796ef0a6d5b7d2e5dd968ad93bbd102d9bf89a797e9bd946c7bf5f5f

Observation bf2732b4-67c7-4f6a-95c7-0b56b7d21034 · outbound

This paper cites mme5: Improving multimodal multilingual embeddings via high-quality synthetic data.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories mme5: Improving multimodal multilingual embeddings via high-quality synthetic data

Reference 6

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source=arxiv_source observed=2026-08-03T01:02:32.750201Z digest=sha256:18ade8410df6ee08f80bd9f6076a4f441969a1a370a52d46981e92a9f12ee169

Observation 3526ed00-8740-452d-a0e9-f03ea2bb870b · outbound

This paper cites Generative thinking, corrective action: User-friendly composed image retrieval via automatic multi-agent collaboration.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Generative thinking, corrective action: User-friendly composed image retrieval via automatic multi-agent collaboration

Reference 7

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source=arxiv_source observed=2026-08-03T01:02:32.802191Z digest=sha256:79b8d0ce96eae3ff1463cdaf54c7ae243a087f02548b99f939b473e56baf5711

Observation fdce8250-ad50-4153-8923-823f3152cbf8 · outbound

This paper cites EmbodiedEval: Evaluate Multimodal LLMs as Embodied Agents.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories EmbodiedEval: Evaluate Multimodal LLMs as Embodied Agents

Reference 8

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source=arxiv_source observed=2026-08-03T01:02:32.859526Z digest=sha256:b6dfab4114912915531bfd8b41d60ebab34ccb4cffe5ed618235fae64f6955f6

Observation 445417bb-7f86-409f-ba75-5d3366f6297d · outbound

This paper cites N., Awasthi, A., Pan, X., Ahuja, C., Mishra, S.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories N., Awasthi, A., Pan, X., Ahuja, C., Mishra, S

Reference 9

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source=arxiv_source observed=2026-08-03T01:02:32.925071Z digest=sha256:7e0dff75c7c5e815b67204581c2a7b0b4aa73d0c84fc260fcf7241cfe055ecc5

Observation 83553ad4-7500-4cc2-b70d-d83a80b48ce5 · outbound

This paper cites Mind2web: Towards a generalist agent for the web.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Mind2web: Towards a generalist agent for the web

Reference 10

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source=arxiv_source observed=2026-08-03T01:02:33.014774Z digest=sha256:b7f691cc40cde39a1f092b5264eb3e0b5e45ddc94d57115502d3e79d2c628eae

Observation 1a166859-1437-4990-b6e9-a382c3b0fc2b · outbound

This paper cites Colpali: Efficient document retrieval with vision language models.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Colpali: Efficient document retrieval with vision language models

Reference 11

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source=arxiv_source observed=2026-08-03T01:02:33.072098Z digest=sha256:6e97c1789327a8545bd24db96deb00e71f3d800a1b4ce995905ed5c212b0f203

Observation 1fe1adda-0ff8-4ee8-810d-001bc1a4585f · outbound

This paper cites A new era of intelligence with Gemini 3.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories A new era of intelligence with Gemini 3

Reference 12

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source=arxiv_source observed=2026-08-03T01:02:33.158432Z digest=sha256:0e554b4ede41ca401bf3f5ff3b1058f8e7727a9794e235f550afe65af450d48d

Observation 20dd5299-2df9-4aa2-b4a3-347238f418c1 · outbound

This paper cites Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge

Reference 13

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source=arxiv_source observed=2026-08-03T01:02:33.277823Z digest=sha256:ab1c7113c5ce10b966904fd80731c0331b96d5e553f6684881a21ac3e5c1c460

Observation 02532e51-fb6a-4e92-8739-f284b0ef4f0b · outbound

This paper cites GPT-4o System Card.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories GPT-4o System Card

Reference 14

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source=arxiv_source observed=2026-08-03T01:02:33.394995Z digest=sha256:aaf8c8e142cbd5a43e979277e6e4410e8505a1880eee3e24f0d3b6c1121ef2d0

Observation 9f24c0db-43fc-4f5d-bd7b-a6602f470807 · outbound

This paper cites V., Sung, Y., Li, Z., and Duerig, T.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories V., Sung, Y., Li, Z., and Duerig, T

Reference 15

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source=arxiv_source observed=2026-08-03T01:02:33.487414Z digest=sha256:25faaeb25135689ab30e794f3522f7977eeb4b1ecd8a84b1e3e18f06798be2c3

Observation 31d3e9fd-d003-4240-b176-73b5528a99b8 · outbound

This paper cites Vlm2vec: Training vision-language models for massive multimodal embedding tasks.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Vlm2vec: Training vision-language models for massive multimodal embedding tasks

Reference 16

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source=arxiv_source observed=2026-08-03T01:02:33.605943Z digest=sha256:662d3500202aa6ca4c6265920f3bc5d2a4e2ee91f63a1d7b76a61f41c65929f0

Observation cc69d2e7-97ed-4dad-90db-293002dc2100 · outbound

This paper cites Crafting papers on machine learning.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Crafting papers on machine learning

Reference 17

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source=arxiv_source observed=2026-08-03T01:02:33.698727Z digest=sha256:e91b18c4ed8441ea69852b98076bcde4256ee7df4269c8403bb881229502ffd9

Observation 15aa4e4e-bea2-4fb9-bdb9-a3d9b3927088 · outbound

This paper cites an unresolved cited work.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-08-03T01:02:33.818381Z digest=sha256:c1173b628ac3d9037f8b27865f6a494f20822fd23aa6a7cc56e69b2b43976c99

Observation 7ded2419-e48c-4485-958d-a9b5d6c385d7 · outbound

This paper cites Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking

Reference 19

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source=arxiv_source observed=2026-08-03T01:02:33.914474Z digest=sha256:e784d5ebcd39643b9bf20248e6e348c07a47f8ab5233a7e6965f453e876fcb01

Observation 32b42022-5d2f-4b8e-9ab1-c7de86b259c1 · outbound

This paper cites MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents

Reference 20

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source=arxiv_source observed=2026-08-03T01:02:34.091340Z digest=sha256:dc631bc030aee5ae6c99582bab9ee13707d9982d255eaa237048dae79838ef95

Observation 38ffbf4b-2e8d-4ba8-ae1a-df91b7c7e20e · outbound

This paper cites Mm-embed: Universal multimodal retrieval with multimodal LLMS.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Mm-embed: Universal multimodal retrieval with multimodal LLMS

Reference 21

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source=arxiv_source observed=2026-08-03T01:02:34.230034Z digest=sha256:c3079153d55435cb57475994cf0c7e0e4adf33820a216e979c455b617c38a0db

Observation 16166113-7826-420e-87a1-7f1c84adfb6b · outbound

This paper cites VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Reference 22

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source=arxiv_source observed=2026-08-03T01:02:34.320848Z digest=sha256:b567b9480d27e951cd7e59d6dcddfb4b56282b99227aaefe766d93e3c6e0f793

Observation 1ac97c6c-3015-4164-ae98-6d82a0434c9c · outbound

This paper cites Introducing GPT-5.2 : The most advanced frontier model for professional work and longrunning agents.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Introducing GPT-5.2 : The most advanced frontier model for professional work and longrunning agents

Reference 23

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source=arxiv_source observed=2026-08-03T01:02:34.417790Z digest=sha256:46ed2391fecafd9143c94a8c6b9b99bbf7655c6dff647005192b0e6890f8e004

Observation d1f48c7d-b670-41b2-9661-828190fdb8db · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., and Sutskever, I.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., and Sutskever, I

Reference 24

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source=arxiv_source observed=2026-08-03T01:02:34.591875Z digest=sha256:84c2a52abed914bb0d9b22b82377c7f065f166aaf4cc5da29a0f6522b3826bd1

Observation 0b387237-72f7-43ce-87b4-bb5e9b8e8374 · outbound

This paper cites Glm-4.5v and glm-4.1v-thinking: Towards versatile multimodal reasoning with scalable reinforcement learning, 2025.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Glm-4.5v and glm-4.1v-thinking: Towards versatile multimodal reasoning with scalable reinforcement learning, 2025

Reference 25

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source=arxiv_source observed=2026-08-03T01:02:34.769100Z digest=sha256:3ad4a92c046a9338d498efc5a441011a443c9f628688e3383bafbc3018e93632

Observation 36d67bfd-7b05-455f-8669-7ddc259737ba · outbound

This paper cites A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., and Li, L.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., and Li, L

Reference 26

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source=arxiv_source observed=2026-08-03T01:02:34.951741Z digest=sha256:0ba80067a12c669e0c7918872f15f70167573f2b7d764ddb522175c8786f4fcf

Observation 9b1c5e39-0d5b-436d-98fc-ec0b8f51f774 · outbound

This paper cites Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval

Reference 27

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source=arxiv_source observed=2026-08-03T01:02:35.070287Z digest=sha256:2358a1dad6ab3f46cb338c852847ac2aa1e83f06cf65683d415b04b22b84cf83

Observation ef29b82e-b6f1-423d-ab3d-17a186663cef · outbound

This paper cites Uniir: Training and benchmarking universal multimodal information retrievers.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Uniir: Training and benchmarking universal multimodal information retrievers

Reference 28

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source=arxiv_source observed=2026-08-03T01:02:35.158045Z digest=sha256:48a3ac01023064ac5b92ca77765531e3c34817cf0faedc41ed203d7760382879

Observation 9fe77158-cac5-4238-a4e8-22e0d2f817b1 · outbound

This paper cites J., Cheng, Z., Shin, D., Lei, F., Liu, Y., Xu, Y., Zhou, S., Savarese, S., Xiong, C., Zhong, V., and Yu, T.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories J., Cheng, Z., Shin, D., Lei, F., Liu, Y., Xu, Y., Zhou, S., Savarese, S., Xiong, C., Zhong, V., and Yu, T

Reference 29

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source=arxiv_source observed=2026-08-03T01:02:35.250679Z digest=sha256:fa015b6bf8e586dc5ae97191410ac78b070ed261b595640a776dfb2c5af06cff

Observation cc4dfd74-5688-4ac3-9319-be2578710aad · outbound

This paper cites A survey on agentic multimodal large language models.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories A survey on agentic multimodal large language models

Reference 30

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source=arxiv_source observed=2026-08-03T01:02:35.310474Z digest=sha256:a0b1c3aba1b846d3ecd95ec3fc67a5c02f82869e9c4d82df16b50626adefd948

Observation 980d3209-a6fa-4191-80b3-f613ddd9f0b7 · outbound

This paper cites A Survey on Multimodal Large Language Models.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories A Survey on Multimodal Large Language Models

Reference 31

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source=arxiv_source observed=2026-08-03T01:02:35.381687Z digest=sha256:ccceffa7a478e69de05f2dec17ae08482e4d85d0c5ee573393c63c186e0410cd

Observation 49d1665b-b035-4f00-a2a9-87125fc03ff8 · outbound

This paper cites Sigmoid loss for language image pre-training.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Sigmoid loss for language image pre-training

Reference 32

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source=arxiv_source observed=2026-08-03T01:02:35.441433Z digest=sha256:8fb03a74474200a17eebde49307ec5321d0dff4a24678c240f45710599305ff4

Observation 6b10a885-a4ba-4dfb-95e3-06b3ed909129 · outbound

This paper cites Magiclens: Self-supervised image retrieval with open-ended instructions.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Magiclens: Self-supervised image retrieval with open-ended instructions

Reference 33

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source=arxiv_source observed=2026-08-03T01:02:35.493635Z digest=sha256:524ba6c617940adb879295facea4d6953568c1dde73672bea34dce705c530938

Observation e00c3eb1-e0f5-4c09-8fb1-7a4805c5d85b · outbound

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

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Reference 34

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source=arxiv_source observed=2026-08-03T01:02:35.562855Z digest=sha256:7225e7474b1ece3bcea795e2a5fa09d6d477802c7c18531f503255ee7de4d361

Observation 3b411d52-5745-4bfb-862b-b6cb155c6133 · outbound

This paper cites V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models

Reference 35

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no resolver link, observed 2026-08-03T01:02:35.623295Z

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source=arxiv_source observed=2026-08-03T01:02:35.623295Z digest=sha256:fdaff5e1c8026f3abc7be68927f1f727d83823d9ec4076e29ba6dba027f4c19b

Observation 8ef789e4-2270-4b6f-a5bc-0b33acecb204 · outbound

This paper cites J., and Lian, D.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories J., and Lian, D

Reference 36

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source=arxiv_source observed=2026-08-03T01:02:35.692722Z digest=sha256:b390ef65473da4dcd62f7ad162c9c0719eb8d0cb72d962d493caacb54612004f

Observation 2ac36528-f433-4fc8-b53f-0c0e46b615e9 · outbound

This paper cites F., Zhu, H., Zhou, X., Lo, R., Sridhar, A., Cheng, X., Ou, T., Bisk, Y., Fried, D., Alon, U., and Neubig, G.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories F., Zhu, H., Zhou, X., Lo, R., Sridhar, A., Cheng, X., Ou, T., Bisk, Y., Fried, D., Alon, U., and Neubig, G

Reference 37

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source=arxiv_source observed=2026-08-03T01:02:35.733752Z digest=sha256:32e875bc6fef00aee6fd950aca5aa3738f2f7c6220a51731e1749708732ffec1

Observation 5b43014d-2eb1-4f58-95f2-60bce1e64fa0 · outbound

This paper cites Large language models for information retrieval: A survey.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories Large language models for information retrieval: A survey

Reference 38

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no resolver link, observed 2026-08-03T01:02:35.736324Z

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source=arxiv_source observed=2026-08-03T01:02:35.736324Z digest=sha256:c4d59b9d52f4c1979b3fd3f38bb83d8886cc5975926f4739f57e83a482c9007c

Observation 933a7374-a2f8-4049-b55b-4cb929bf10af · outbound

This paper cites write newline.

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories write newline

Reference 39

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Pith citing papers

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