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Paper Citation Record · LEDGER

PyVision: Agentic Vision with Dynamic Tooling

As of 22 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 33 inbound Pith citation observations for arXiv:2507.07998.

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

pith.paper-citation-record.v1
2507.07998 v3

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:31:32.699506Z

measured 94 of 94 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:31:27.386319Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

61 of 61 outbound references displayed

  • verified exact1
  • verified fuzzy34
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation a5afcafc-0273-46ad-be4e-927e30c5f5b6 · outbound

This paper cites Kimi k2: Open agentic intelligence, 2025.

PyVision: Agentic Vision with Dynamic Tooling Kimi k2: Open agentic intelligence, 2025

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.973594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:27.077412Z digest=sha256:a6d7c647d51a0e1eadb592ca65253faa4b69fa129ab9c1620fd8bae0063a8937

Observation a80a638c-e8f9-4bf8-a0e3-225a37e9b62d · outbound

This paper cites Neural Module Networks.

PyVision: Agentic Vision with Dynamic Tooling Neural Module Networks

Reference 2

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local_arxiv, observed 2026-08-06T18:31:33.015212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:27.169584Z digest=sha256:361dca6d05437f4f045b41dd56560e766ae57bafec64f4fb1f347aed553e9466

Observation f30aee14-a097-4513-9c8b-36d38b30948b · outbound

This paper cites Introducing claude 4, 2025.

PyVision: Agentic Vision with Dynamic Tooling Introducing claude 4, 2025

Reference 3

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no resolver link, observed 2026-08-06T18:31:27.255136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:27.255136Z digest=sha256:858469bba45d3f6d8ac5fc786198a13347d025b996efb2f536ecd6d61fb606e0

Observation b4ffdfc9-7646-4a7d-b84c-26b6d3f8d008 · outbound

This paper cites Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents.

PyVision: Agentic Vision with Dynamic Tooling Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents

Reference 4

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no resolver link, observed 2026-08-06T18:31:27.304146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:27.304146Z digest=sha256:6fe6a5e5b62288430bbb1e03bc9b48e6b818fb5c97cb7a2854d5a06372fa17ab

Observation c4fbe6ac-4f8d-4c09-81e4-0ba531d0c67f · outbound

This paper cites Digirl: Training in-the-wild device-control agents with autonomous reinforcement learning.

PyVision: Agentic Vision with Dynamic Tooling Digirl: Training in-the-wild device-control agents with autonomous reinforcement learning

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.962785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:27.397892Z digest=sha256:54fa1958b2ea21f76f6ef1df50c4d141df6f8015fbb870f7fe5c434b49654cde

Observation 5db962fc-95de-4409-8749-377fe7432f98 · outbound

This paper cites Qwen2.5-VL Technical Report.

PyVision: Agentic Vision with Dynamic Tooling Qwen2.5-VL Technical Report

Reference 6

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no resolver link, observed 2026-08-06T18:31:27.491410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:27.491410Z digest=sha256:1b78adf280cd60eda5fe0402b1fc51273f547d68d312383d5b55ddfef766a352

Observation b9d58846-db9a-453a-a287-9883022856e6 · outbound

This paper cites The opencv library.

PyVision: Agentic Vision with Dynamic Tooling The opencv library

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:27.597930Z digest=sha256:1bdb044eda26e5ab5a255f378687819182dd58ff9b354a55cf1b83b64b012fbd

Observation 8c07f8b5-7ea0-48c1-afd3-47702aeea6f2 · outbound

This paper cites Pillow (pil fork) documentation.

PyVision: Agentic Vision with Dynamic Tooling Pillow (pil fork) documentation

Reference 8

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raw_fallback, observed 2026-08-06T18:31:33.947488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:27.697862Z digest=sha256:403f6f37adc2cc5139d5b38380cd4e96047ffc7c9fcdf488974d958c348640ad

Observation cd54909f-3672-4014-a516-d6a0f2ee7e97 · outbound

This paper cites ReTool: Reinforcement Learning for Strategic Tool Use in LLMs.

PyVision: Agentic Vision with Dynamic Tooling ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:27.776963Z digest=sha256:b94a16f73ae517fecbd09bebaa29033db41bfe100816a0c291f97d9d262c93c0

Observation d2041e0f-4789-4dc9-a2fa-2e6095c464d8 · outbound

This paper cites The parable of the parser, 2024.

PyVision: Agentic Vision with Dynamic Tooling The parable of the parser, 2024

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.940571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:27.867133Z digest=sha256:485b917782196f5951ac9555b10d15bf45212ac9597a8f2df01e296a07b7fb15

Observation e4c05125-3774-4e47-9910-2e3534eae56b · outbound

This paper cites ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving.

PyVision: Agentic Vision with Dynamic Tooling ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving

Reference 11

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source=pdf_text observed=2026-08-06T18:31:27.922955Z digest=sha256:181b7b90e254f89d743ebccab03397a5b8101d8f16655d503633439285b1cfd9

Observation ad422b48-9cb7-4c5d-a36e-dfbd4c9192ac · outbound

This paper cites Visual programming: Compositional visual reasoning without training.

PyVision: Agentic Vision with Dynamic Tooling Visual programming: Compositional visual reasoning without training

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.934584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:27.996844Z digest=sha256:e7124ffd26ecedbbb75e5bad5161f2e07c4db471924999668d0c619f762ca139

Observation 5d2c54b4-e500-41c6-a148-545b0ddcac12 · outbound

This paper cites Array programming with numpy.

PyVision: Agentic Vision with Dynamic Tooling Array programming with numpy

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.928141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:28.091639Z digest=sha256:bb56a1bc9c8c6bfd66e6ff7e61c9a9931a8c20117376f6c81a45a67c72687728

Observation f8c2b910-1721-4eac-a620-ee4d592ff6bf · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

PyVision: Agentic Vision with Dynamic Tooling MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:28.170478Z digest=sha256:aec789a3ab2dfbf64ee987de48f0923c7bc229ec040eb49fd0d4919fdb08a5ab

Observation 7014bf67-8f38-4df1-9242-69d7d769e6f9 · outbound

This paper cites Cogagent: A visual language model for gui agents.

PyVision: Agentic Vision with Dynamic Tooling Cogagent: A visual language model for gui agents

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.921080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:28.270742Z digest=sha256:37831a8b6466c10e08eed60b110873df7e9abdde913f397c7fd5554ab5c9b5e1

Observation c1742524-cab3-455d-ad94-c969dd422554 · outbound

This paper cites OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation.

PyVision: Agentic Vision with Dynamic Tooling OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Reference 16

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no resolver link, observed 2026-08-06T18:31:28.376138Z

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source=pdf_text observed=2026-08-06T18:31:28.376138Z digest=sha256:c2ccc0b3caa708cafbed8dda93c0e4961c4137bc07719837f1d7df6bbae5d5d6

Observation 6a972770-ac20-4c00-b7c2-eccad7edc989 · outbound

This paper cites Smith, and Ranjay Krishna.

PyVision: Agentic Vision with Dynamic Tooling Smith, and Ranjay Krishna

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.915062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:28.465637Z digest=sha256:0e8bb88f197031803c5d7d0492421ab0d8399e4d87b43049b9b19479fb82c93b

Observation 442b0998-98f2-4841-b469-03ae1c093bef · outbound

This paper cites OmniMedVQA: A new large-scale comprehensive evaluation benchmark for medical lvlm.

PyVision: Agentic Vision with Dynamic Tooling OmniMedVQA: A new large-scale comprehensive evaluation benchmark for medical lvlm

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.908647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:28.552947Z digest=sha256:481929351acc814ec75579d279cb62e0488b8d293a7f003c50578915772a606b

Observation ed42a9dc-793f-4ef2-a7d0-9eeafbb72508 · outbound

This paper cites The ebbinghaus illusion: New contextual effects and theoretical considerations.

PyVision: Agentic Vision with Dynamic Tooling The ebbinghaus illusion: New contextual effects and theoretical considerations

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:28.647615Z digest=sha256:54a2d32df5350fe324f61a8e73c0861d96e3cac2a45420114411fcf27c21c760

Observation b03bbfd6-b3cb-49de-9bd2-9892b6d89df1 · outbound

This paper cites Lawrence Zitnick, and Ross B.

PyVision: Agentic Vision with Dynamic Tooling Lawrence Zitnick, and Ross B

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.895814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:28.736999Z digest=sha256:5abedfd85d143fb81ea338fd095a474e4fcae0180b50de50863c4e3f7bf57939

Observation 75cf7c89-1322-4def-b4df-108e483bfa8c · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick.

PyVision: Agentic Vision with Dynamic Tooling Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:28.797780Z digest=sha256:c66fb3cd31744164d9382f6e3419ca79ccfab76e86588d09d9e3c5a03f40e4c1

Observation 3fdb7487-9e38-4bb6-84f8-8b04c1c3b3f8 · outbound

This paper cites Large language models are zero-shot reasoners.

PyVision: Agentic Vision with Dynamic Tooling Large language models are zero-shot reasoners

Reference 22

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source=pdf_text observed=2026-08-06T18:31:28.982833Z digest=sha256:7196d3e48b0ea09e54279b24b1f70af30520bd6857dc61fdc0ff72ba6c56f6df

Observation 931ee908-e07d-44a4-808b-0b59cd8eaf9b · outbound

This paper cites Geochat: Grounded large vision-language model for remote sensing.

PyVision: Agentic Vision with Dynamic Tooling Geochat: Grounded large vision-language model for remote sensing

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.881818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:29.104543Z digest=sha256:4b9474e1d6d1f0ce9f2deddc53b1260a5c1267eaab5ec21ab60efce68397a511

Observation fb6c728a-b29f-46e4-8081-9b8b5be409b5 · outbound

This paper cites Visual abstract thinking empowers multimodal reasoning.

PyVision: Agentic Vision with Dynamic Tooling Visual abstract thinking empowers multimodal reasoning

Reference 24

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source=pdf_text observed=2026-08-06T18:31:29.279722Z digest=sha256:9dff9854f368f08c826ed46d31c65b9bc082067a477b39d47335661f8ab0c822

Observation ee192e53-b4e5-455a-bd98-c1a2e3858031 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.

PyVision: Agentic Vision with Dynamic Tooling Grounding dino: Marrying dino with grounded pre-training for open-set object detection

Reference 25

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raw_fallback, observed 2026-08-06T18:31:33.874844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:29.433590Z digest=sha256:e27f911fa868e6c555c6d9364418a1204a050876f72d5f47531fbe4150febc50

Observation f2e3bad0-969e-4e2e-9f1a-1d30fcfc864d · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

PyVision: Agentic Vision with Dynamic Tooling MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 26

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source=pdf_text observed=2026-08-06T18:31:29.589394Z digest=sha256:bc5173b1a27528c0ab33c138c268cb0ad76e8fb9e3afd2d3922a610034359fbc

Observation 344d5012-de0d-4b14-96a2-56ceeb213ae0 · outbound

This paper cites OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning.

PyVision: Agentic Vision with Dynamic Tooling OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning

Reference 27

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no resolver link, observed 2026-08-06T18:31:29.760587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:29.760587Z digest=sha256:3475ac96d2dede79aa5cf35b141ff679ac89589dfccbda6653e60a20f47dca4c

Observation 6a59b88d-55d9-4c94-b67c-ab45b12a7114 · outbound

This paper cites Deepswe: Training a state-of- the-art coding agent from scratch by scaling rl, 2025.

PyVision: Agentic Vision with Dynamic Tooling Deepswe: Training a state-of- the-art coding agent from scratch by scaling rl, 2025

Reference 28

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raw_fallback, observed 2026-08-06T18:31:33.868413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:29.928911Z digest=sha256:3796ad51e1383a53124ac1c68120bc2e55b720147b8f1133d0c8e9220af0ac24

Observation e1d7d82c-601a-411f-9a72-66e0f4ea3dcf · outbound

This paper cites Meet genspark super agent, 2025.

PyVision: Agentic Vision with Dynamic Tooling Meet genspark super agent, 2025

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.861776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.044613Z digest=sha256:851777b13ce841b21c46b1658f412950ccec207bdb1266826a21984c81466ebe

Observation 197a3540-5274-497d-a21c-fa29b0e68979 · outbound

This paper cites Leave it to manus, 2025.

PyVision: Agentic Vision with Dynamic Tooling Leave it to manus, 2025

Reference 30

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raw_fallback, observed 2026-08-06T18:31:33.854518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.241670Z digest=sha256:b7fc7da1f4908193a43ceb0a661cecd5a8c76945e42814c05c0db6c69c9c86af

Observation 2e74621c-771a-43e2-b2f2-0171f3cc1d8c · outbound

This paper cites pandas: a foundational python library for data analysis and statistics.

PyVision: Agentic Vision with Dynamic Tooling pandas: a foundational python library for data analysis and statistics

Reference 31

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raw_fallback, observed 2026-08-06T18:31:33.848306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.365414Z digest=sha256:d64065eff2673df4f2d5874c3616a8586a3a34a69f6151ff440eca35bbdf0d69

Observation 4b7ce66d-2765-475c-8809-aa5104cb95b0 · outbound

This paper cites Minimax-agent, 2025.

PyVision: Agentic Vision with Dynamic Tooling Minimax-agent, 2025

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.840890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.453205Z digest=sha256:c53646a9c5d0fd3032c47e40c03c44aba12820bddae3f167781773f71f5d675b

Observation 469f1617-f211-4f2a-a0f3-80e867d7c3f7 · outbound

This paper cites Computer-using agent, 2025.

PyVision: Agentic Vision with Dynamic Tooling Computer-using agent, 2025

Reference 33

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raw_fallback, observed 2026-08-06T18:31:33.834843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.567637Z digest=sha256:d9100d72df161fc19438018d281866857a83b52c6fecfea0626b2e423360c41e

Observation b7f2d26a-3c5c-4bc4-b2a8-6f2877ab00eb · outbound

This paper cites Introducing codex, 2025.

PyVision: Agentic Vision with Dynamic Tooling Introducing codex, 2025

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.828605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.636081Z digest=sha256:b505036d3dc2399e4ef7a7e493bc0faaa09840b71f1cb094cc3f4afdfacf5e61

Observation 83171dec-3f29-444b-86d9-a074486d7b60 · outbound

This paper cites Introducing gpt-4.1 in the api, 2025.

PyVision: Agentic Vision with Dynamic Tooling Introducing gpt-4.1 in the api, 2025

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:30.720310Z digest=sha256:e11b7d813e4ec83613506e8d581f8688d036210bd90a791021d61ef355ef7b92

Observation 20a06f0f-2bb5-4b71-872f-075f80a2e6cf · outbound

This paper cites New embedding models and api updates, 2025.

PyVision: Agentic Vision with Dynamic Tooling New embedding models and api updates, 2025

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.817040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.785546Z digest=sha256:4cf905de0719f14a298b8ad71ea534a1de2ce99227ae75091c98341a5c68781a

Observation e6af9d75-02e2-41fa-bdda-ede0a940b1af · outbound

This paper cites Thinking with images, 2025.

PyVision: Agentic Vision with Dynamic Tooling Thinking with images, 2025

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:30.868992Z digest=sha256:96596cdeb97f40652a07d7e9ccc542035e8f208ba47d5099dac510fe40f752b4

Observation a6d639d8-be91-4f6c-95e3-cc78812f599d · outbound

This paper cites Scikit-learn: Machine learning in python.

PyVision: Agentic Vision with Dynamic Tooling Scikit-learn: Machine learning in python

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.805786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:30.928543Z digest=sha256:7eaf79e618a3b7717c3187e15d37a22f51256dc5d1d7e9a0b62089c464831838

Observation 9ac8b27e-f1aa-46b4-a416-0fb5fe86ec40 · outbound

This paper cites Cogcom: A visual language model with chain-of- manipulations reasoning.

PyVision: Agentic Vision with Dynamic Tooling Cogcom: A visual language model with chain-of- manipulations reasoning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.798943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:31.006095Z digest=sha256:015e0f71f92660ad1d6f20ba4950566f6e8958ec00a6459f153607da2410a7bc

Observation 07a5976d-7bf5-4425-adb5-f7a9316b6d16 · outbound

This paper cites Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution.

PyVision: Agentic Vision with Dynamic Tooling Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution

Reference 40

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no resolver link, observed 2026-08-06T18:31:31.069199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.069199Z digest=sha256:4c3cd64ee5c4f81d69fe364480ecc01dde7b8b1b68a204959417161b1ab3e99e

Observation 70cecc8f-284a-4e32-af48-ed0145684eef · outbound

This paper cites Vision language models are blind.

PyVision: Agentic Vision with Dynamic Tooling Vision language models are blind

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.791558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:31.152704Z digest=sha256:90b273d616b5ea0fbc8e30f6105084a2cb29baab3892a5794f088fd8d9962bec

Observation 407671b6-0559-4652-9b9e-8f4ea6a3d8e5 · outbound

This paper cites Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face.

PyVision: Agentic Vision with Dynamic Tooling Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face

Reference 42

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no resolver link, observed 2026-08-06T18:31:31.218655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.218655Z digest=sha256:94427354d6d6308191f159e9cfb016a83c787928beea5da5bb26a1b1b8cdf284

Observation 1bd79913-9728-404c-a379-a26deb8e6c40 · outbound

This paper cites VisualPuzzles: Decoupling Multimodal Reasoning Evaluation from Domain Knowledge.

PyVision: Agentic Vision with Dynamic Tooling VisualPuzzles: Decoupling Multimodal Reasoning Evaluation from Domain Knowledge

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T18:31:31.285831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.285831Z digest=sha256:8e0d635a60cdbb81160e856b9e1e61413be8b6711ba9b48b2037ec6b39466341

Observation 9b3771f1-cd2f-4d07-bf09-17bdae05c6aa · outbound

This paper cites Pixel reasoner: Incentivizing pixel-space reasoning with curiosity-driven reinforcement learning, 2025.

PyVision: Agentic Vision with Dynamic Tooling Pixel reasoner: Incentivizing pixel-space reasoning with curiosity-driven reinforcement learning, 2025

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.780989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:31.399968Z digest=sha256:baadab756ca287ffd1fcd1c75513630d2a7e758dfff49f932d75df5fd29fe371

Observation bb083771-b684-4103-8f26-0be9d6397546 · outbound

This paper cites OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning.

PyVision: Agentic Vision with Dynamic Tooling OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning

Reference 45

Resolution
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no resolver link, observed 2026-08-06T18:31:31.459660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.459660Z digest=sha256:b02b607169c08539d00232d0fd271b5459fee50b962453c5ae3b43805dec41b4

Observation 375eccfd-7c3a-4b25-bb69-bf1e8de3b612 · outbound

This paper cites Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers.

PyVision: Agentic Vision with Dynamic Tooling Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers

Reference 46

Resolution
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no resolver link, observed 2026-08-06T18:31:31.545459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.545459Z digest=sha256:8669a815f7494abbf39503ac2f0a0addc31326660fde15d648691d576089987e

Observation 2512fa8c-dac7-4c13-b574-cf182776f8d5 · outbound

This paper cites Vipergpt: Visual inference via python execution for reasoning.

PyVision: Agentic Vision with Dynamic Tooling Vipergpt: Visual inference via python execution for reasoning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.774092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:31.625996Z digest=sha256:e96c5f1119eaba76fac0bb93d052202b3fe5934a90117ad1394f975e98c8257e

Observation c722fbc1-6f37-4a7b-8cdc-f2b80c527ab4 · outbound

This paper cites scikit-image: image processing in python.

PyVision: Agentic Vision with Dynamic Tooling scikit-image: image processing in python

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.767157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:31.713736Z digest=sha256:e533491d5c59e59345dc96d043d3cadf29bd593c332f6878a21013ba3eb64e91

Observation 8db69a04-3847-4937-b68e-7e3248bd8f72 · outbound

This paper cites Measuring multimodal mathematical reasoning with math-vision dataset.

PyVision: Agentic Vision with Dynamic Tooling Measuring multimodal mathematical reasoning with math-vision dataset

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.759629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:31.775470Z digest=sha256:0c86adb62cc1daeb39b6b705ca4ab418a796c68b1f515385c3843b1d597b3038

Observation 4b6f3055-33ec-493a-99dd-05ba07a17155 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

PyVision: Agentic Vision with Dynamic Tooling Chain-of-thought prompting elicits reasoning in large language models

Reference 50

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no resolver link, observed 2026-08-06T18:31:31.843117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.843117Z digest=sha256:e6340b2aed8606558f097f2bbb7ad540b141337c72eb344b48af3a66e53d5e1a

Observation e0b244c4-a05d-424d-b512-b052d4c75723 · outbound

This paper cites Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models.

PyVision: Agentic Vision with Dynamic Tooling Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

Reference 51

Resolution
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no resolver link, observed 2026-08-06T18:31:31.892144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.892144Z digest=sha256:36c8bca37f0ee99aff8048585144ada760ade1d4089015f9517a1ef3e5c394c2

Observation 09842a97-163d-4cc7-b5ea-5b173c0b839c · outbound

This paper cites V*: Guided visual search as a core mechanism in multimodal llms.

PyVision: Agentic Vision with Dynamic Tooling V*: Guided visual search as a core mechanism in multimodal llms

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T18:31:31.951813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:31.951813Z digest=sha256:f7c909f7f31c340e6246460b56eb5429ca47b6f667f2c649cd67b389c4bf0f16

Observation 44ef97f2-5ca7-4ce4-a1d2-f6d557a1229f · outbound

This paper cites Simpletir: End-to-end reinforcement learning for multi-turn tool-integrated reasoning, 2025.

PyVision: Agentic Vision with Dynamic Tooling Simpletir: End-to-end reinforcement learning for multi-turn tool-integrated reasoning, 2025

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.668710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:32.034774Z digest=sha256:4bbddc655a4bbc73f9d6a287d37801f3c95c1fd7cbea7ec767fe6bffd4dc9fbf

Observation 52f10a0c-59d5-4d79-9771-72c77fa415a1 · outbound

This paper cites Set-of- mark prompting unleashes extraordinary visual grounding in gpt-4v, 2023.

PyVision: Agentic Vision with Dynamic Tooling Set-of- mark prompting unleashes extraordinary visual grounding in gpt-4v, 2023

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.661583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:32.141264Z digest=sha256:4eb903c6b804e486df53509abf74421c121f5c7acad36ebc22cfed7421bb7034

Observation ea9b7267-1f8b-4c22-bfd2-8c3fd6f69ba9 · outbound

This paper cites Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces.

PyVision: Agentic Vision with Dynamic Tooling Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces

Reference 55

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no resolver link, observed 2026-08-06T18:31:32.209763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:32.209763Z digest=sha256:5a6c87ac701008342070a0dcdb491f6a4a3878f7660f50bfe2d70cc924f9a72d

Observation ed78da75-e34c-4141-b2ca-788110a7c126 · outbound

This paper cites MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action.

PyVision: Agentic Vision with Dynamic Tooling MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Reference 56

Resolution
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no resolver link, observed 2026-08-06T18:31:32.295973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:32.295973Z digest=sha256:77ceb16dc846f6d335c5c22ec136426771e5ede52d8c5b9a93e2a1bc4c6a2f09

Observation c1d640ce-e04a-42f2-9e85-048d4473b3b0 · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi.

PyVision: Agentic Vision with Dynamic Tooling Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi

Reference 57

Resolution
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no resolver link, observed 2026-08-06T18:31:32.362317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:32.362317Z digest=sha256:df3a104a5b9b82c9eadac6e74493478fe112d2062be84504310dc8d604ab2801

Observation 38e358a9-a6f5-4292-8674-7ad28c74549f · outbound

This paper cites Chain-of-focus: Adaptive visual search and zooming for multimodal reasoning via rl, 2025.

PyVision: Agentic Vision with Dynamic Tooling Chain-of-focus: Adaptive visual search and zooming for multimodal reasoning via rl, 2025

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.649987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:32.424110Z digest=sha256:3d7ab0b4410d8ebc669030e247e778633639d779bb39d29dd9bf9f2bd7b270e3

Observation 720b592a-6898-41c2-8f2b-40f2d7204a90 · outbound

This paper cites Gpt-4v(ision) is a generalist web agent, if grounded, 2024.

PyVision: Agentic Vision with Dynamic Tooling Gpt-4v(ision) is a generalist web agent, if grounded, 2024

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.557958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:32.542380Z digest=sha256:6d06447c242d116b8732377d6a1ef1e9830ecf2612c2298f28a5dfb514c12372

Observation 8461bda1-210c-4f72-8b3e-370dcff5b415 · outbound

This paper cites thinking with images.

PyVision: Agentic Vision with Dynamic Tooling thinking with images

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:31:33.324538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:31:32.636059Z digest=sha256:9a718d6cf5f6d2fba205745842e4e4dfe1d3c82e8b84cc377ca07c06171a270a

Observation d9b923a5-6bbe-4d9a-8f47-361dc0d74855 · outbound

This paper cites Image-of-Thought Prompting for Visual Reasoning Refinement in Multimodal Large Language Models.

PyVision: Agentic Vision with Dynamic Tooling Image-of-Thought Prompting for Visual Reasoning Refinement in Multimodal Large Language Models

Reference 61

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no resolver link, observed 2026-08-06T18:31:32.699506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:31:32.699506Z digest=sha256:91a50d7023db825e5c3304d8ccdf20b8dd04a77bd40b682505bcf9532e63b5cf

Pith citing papers

Observation af2c8f61-5ca4-4d2f-a1c4-f5ebfe77fa78 · inbound

WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent cites this paper.

WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent PyVision: Agentic Vision with Dynamic Tooling

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T18:56:24.044382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-15T18:56:23.817544Z digest=sha256:12715135121d9c8b6dd56d0b64d155e915ad423eb820c308167d967fd91a24ac

Observation 2794f6a5-d80c-424d-89cc-d2c57922a9a4 · inbound

Reinforced Visual Perception with Tools cites this paper.

Reinforced Visual Perception with Tools PyVision: Agentic Vision with Dynamic Tooling

Reference 64

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no resolver link, observed 2026-08-05T12:27:05.095242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T12:27:05.095242Z digest=sha256:62c34f56d92cdb470f644d27b0849465b2bc2bc6851174552c97eeb314e8d8e2

Observation eeb6d542-26f1-4307-9f40-689f54634db2 · inbound

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey PyVision: Agentic Vision with Dynamic Tooling

Reference 251

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verified exact
arxiv_id, observed 2026-05-18T19:21:48.220855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T19:19:36.427337Z digest=sha256:dd97ae9233d5ff4ebb3879737a3cd5ebca84dca721d06f1fe8fe8512595fe965

Observation ddcf5c82-9bc7-460c-bc01-5b77b2822ba8 · inbound

Visual Programmability: A Guide for Code-as-Thought in Chart Understanding cites this paper.

Visual Programmability: A Guide for Code-as-Thought in Chart Understanding PyVision: Agentic Vision with Dynamic Tooling

Reference 66

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unresolved
no resolver link, observed 2026-08-04T19:27:21.033838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:27:21.033838Z digest=sha256:56ea65cfbacae8042cdb5b3dd60c378a968860ecba4910122e5df2b79c10517b

Observation 235dc788-36cb-4be8-ba9e-596e3c1590d3 · inbound

MGA: Memory-Driven GUI Agent for Observation-Centric Interaction cites this paper.

MGA: Memory-Driven GUI Agent for Observation-Centric Interaction PyVision: Agentic Vision with Dynamic Tooling

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:40:50.740545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T03:38:30.442712Z digest=sha256:dfb1a6dac1bdf416650fcdf9305ab18dc4342a5f5c5850bf5bc7dee038a61910

Observation 6931f53b-e1be-4109-bb6b-c72606bd812b · inbound

DeepEyesV2: Toward Agentic Multimodal Model cites this paper.

DeepEyesV2: Toward Agentic Multimodal Model PyVision: Agentic Vision with Dynamic Tooling

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-16T05:32:29.498700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T05:32:29.266583Z digest=sha256:55f67589bd97bf89f663797b26cad3cdb408a5d2fedbde1601fe1e56a1cd72f4

Observation f94170cf-b049-48b5-851d-c6adbd6ef2f7 · inbound

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection cites this paper.

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection PyVision: Agentic Vision with Dynamic Tooling

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:41:17.866262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T21:39:46.031368Z digest=sha256:21fe5d762f677c8d6b2655aadd0839cc9c0c182800a224749313f6bcd6fd0767

Observation e6390c02-024f-4951-900c-3745f142cba6 · inbound

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection cites this paper.

Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection PyVision: Agentic Vision with Dynamic Tooling

Reference 49

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unresolved
no resolver link, observed 2026-08-03T15:38:31.825682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:38:31.825682Z digest=sha256:9efae1f030298152664e029bd4dd6e0d480fa6f195a12dbc2aab2313bbc7544c

Observation b0f77327-d9e3-4bf3-aae6-3e1fe95c4ef6 · inbound

GeoBrowse: A Geolocation Benchmark for Agentic Tool Use with Expert-Annotated Reasoning Traces cites this paper.

GeoBrowse: A Geolocation Benchmark for Agentic Tool Use with Expert-Annotated Reasoning Traces PyVision: Agentic Vision with Dynamic Tooling

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:33:02.367416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T17:31:08.575993Z digest=sha256:7958a73a8c5b959da5a2ba9ea312c2840ef74897db1d7b33176a8f00fe08b5da

Observation 41db582d-b477-4a42-ac40-35de59172d73 · inbound

Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models cites this paper.

Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models PyVision: Agentic Vision with Dynamic Tooling

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:20:53.921822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T18:35:21.514502Z digest=sha256:6d596308c9a6b7d90976386575c189f4f5e2f2540968a998ef6c7f9c49241666

Observation 0775de81-2189-4ba6-924b-93656a0fa437 · inbound

Seek-and-Solve: Benchmarking MLLMs for Visual Clue-Driven Reasoning in Daily Scenarios cites this paper.

Seek-and-Solve: Benchmarking MLLMs for Visual Clue-Driven Reasoning in Daily Scenarios PyVision: Agentic Vision with Dynamic Tooling

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T13:05:24.607064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T13:04:34.328439Z digest=sha256:a37f86bd7bec68390251b84335f89c7211750bdae6ff8e25f08a64466158f3cc

Observation 841f10ab-b868-4e84-87fb-afda973faa5f · inbound

EVE: Verifiable Self-Evolution of MLLMs via Executable Visual Transformations cites this paper.

EVE: Verifiable Self-Evolution of MLLMs via Executable Visual Transformations PyVision: Agentic Vision with Dynamic Tooling

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:25:54.895084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T05:23:45.814042Z digest=sha256:b6f8d195e4148b3b7426662dc147f29bb7f447da0a65b6a2d184c0aea7974b84

Observation af524508-e32c-48e9-9fda-b106791a3c8b · inbound

Global Context or Local Detail? Adaptive Visual Grounding for Hallucination Mitigation cites this paper.

Global Context or Local Detail? Adaptive Visual Grounding for Hallucination Mitigation PyVision: Agentic Vision with Dynamic Tooling

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:46:19.359514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T04:29:59.246652Z digest=sha256:fd364d1daa0de0da0e8296d07b0a8e0483cb396fc0de8d2ff4353d021f78536f

Observation e85b6812-221f-4d2e-8405-af76f84ecb69 · inbound

Self-Consistent Latent Reasoning: Long Latent Sequence Reasoning for Vision-Language Model cites this paper.

Self-Consistent Latent Reasoning: Long Latent Sequence Reasoning for Vision-Language Model PyVision: Agentic Vision with Dynamic Tooling

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:17:29.015867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T07:14:48.918959Z digest=sha256:2dea64d2d4908e8b7f414d07ffc0c8b15edbc766a533421ce55d254f70013467

Observation 70b25b87-4e6b-4b36-8c7c-20f52e9f7855 · inbound

Self-Consistent Latent Reasoning: Long Latent Sequence Reasoning for Vision-Language Model cites this paper.

Self-Consistent Latent Reasoning: Long Latent Sequence Reasoning for Vision-Language Model PyVision: Agentic Vision with Dynamic Tooling

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:48:00.482768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-14T21:47:50.595481Z digest=sha256:f38e41998a5c5ad126a853ce5f248334cf642d335728f455fd9e668397549b79

Observation b5e4f74f-65fd-4dbc-b399-6da1e8d3ab65 · inbound

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models cites this paper.

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models PyVision: Agentic Vision with Dynamic Tooling

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:22:28.554337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-13T07:21:40.803291Z digest=sha256:a4173da2f6f1add747cc11596d88034e439221ed8baad4427a160a4eeaa6f3ea

Observation 564a1284-f010-46ab-bcad-814caa943e57 · inbound

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models cites this paper.

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models PyVision: Agentic Vision with Dynamic Tooling

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:52:40.196796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-19T16:48:20.132240Z digest=sha256:256e612a235e7af6da1ac375f5c6a124e40a6674d33bd4d4ee52c19d4513a405

Observation b473b66f-281c-4dd4-87e1-114512777c74 · inbound

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models cites this paper.

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models PyVision: Agentic Vision with Dynamic Tooling

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:04:02.654171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-21T08:02:00.980836Z digest=sha256:a0f55718f29334e72a583544908899401e4bf3e3e4c30730903fc3e7924264b7

Observation be86f9df-0920-4262-bd4e-84d1cb2c1cdc · inbound

Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models cites this paper.

Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models PyVision: Agentic Vision with Dynamic Tooling

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-20T18:48:53.457068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T18:44:54.835575Z digest=sha256:e5901bf4b7298cb25dbae918ae5036848ef82aac300666d980d13b3457ad0901

Observation c30a972a-050c-4254-b6a1-64422ca970f8 · inbound

VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation cites this paper.

VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation PyVision: Agentic Vision with Dynamic Tooling

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-20T19:38:56.208850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T19:37:09.244578Z digest=sha256:50921f1f4771adda68aa069520f33289c15549f45b5512f6f010418b2a3fe535

Observation 40d11c3d-9144-48a4-81d0-1fb4e9adb112 · inbound

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools cites this paper.

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools PyVision: Agentic Vision with Dynamic Tooling

Reference 111

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:33:58.460480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-21T05:33:30.670201Z digest=sha256:5b58065c8151db51e1ca2202603377f4408b261f549dfbc05557aa484f8b57ce

Observation 4f90158f-42be-4726-884e-0c39e13cd00e · inbound

Agent Explorative Policy Optimization for Multimodal Agentic Reasoning cites this paper.

Agent Explorative Policy Optimization for Multimodal Agentic Reasoning PyVision: Agentic Vision with Dynamic Tooling

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T12:23:23.716945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-29T12:22:39.655615Z digest=sha256:bc58d59455db0c4f6a0cd54adcfdd8461a82dc7d782524e0afff6f2840a6e48d

Observation f11e5175-6788-4959-a676-2fa09fcf2b28 · inbound

VESTA: Visual Exploration with Statistical Tool Agents cites this paper.

VESTA: Visual Exploration with Statistical Tool Agents PyVision: Agentic Vision with Dynamic Tooling

Reference 58

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:56:10.491561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T21:58:11.339217Z digest=sha256:934c08fbb5fb22e6b9e1419080751ada31fdb19b36b7944d763c75647599aa5e

Observation 0d3cdffa-618b-4f0d-b3fd-13a59f6767cb · inbound

DeepLatent: Think with Images via Parallel Latent Visual Reasoning cites this paper.

DeepLatent: Think with Images via Parallel Latent Visual Reasoning PyVision: Agentic Vision with Dynamic Tooling

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-28T20:22:37.736027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-28T18:44:39.545911Z digest=sha256:d45d5221e9ee39897272f1fa41c7370b9c0aafa15532ab7c26b89e718cbc6c40

Observation f131c95a-ed36-496c-a213-3e8aeaa16c58 · inbound

Statistically Reliable LLM-Based Ranking Evaluation via Prediction-Powered Inference cites this paper.

Statistically Reliable LLM-Based Ranking Evaluation via Prediction-Powered Inference PyVision: Agentic Vision with Dynamic Tooling

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-02T06:06:41.655865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-28T07:32:49.400704Z digest=sha256:8d8570bfd26a0e34e69a92caee0498b065c8bef3fb8e71418f0745e585d79121

Observation c3c789f7-cd13-4ebc-a23d-15e19d8aaa67 · inbound

Look Light, Think Heavy: What Multimodal Chain-of-Thought Reasoning Can and Cannot Do cites this paper.

Look Light, Think Heavy: What Multimodal Chain-of-Thought Reasoning Can and Cannot Do PyVision: Agentic Vision with Dynamic Tooling

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T09:09:43.191017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T10:27:43.396559Z digest=sha256:2fb2cbe1c8bb01c7d7f962c3b79898f5962d35910e04e1997eefd0b7da19f492

Observation 67fd6d48-7df4-4e46-af2a-04017a69c05f · inbound

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models PyVision: Agentic Vision with Dynamic Tooling

Reference 149

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:09:55.245087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T01:50:54.242508Z digest=sha256:b3d575668ba0dc3f2f0577f1ee33d5a0deb63636e9c8a80c32ac0c7ed92be6f1

Observation 63a62b00-6ced-4f98-8e12-1e0f1365632e · inbound

Latent Noise Mask for Reducing Visual Redundancy in Multimodal Large Language Models cites this paper.

Latent Noise Mask for Reducing Visual Redundancy in Multimodal Large Language Models PyVision: Agentic Vision with Dynamic Tooling

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:44:19.804975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T06:35:16.868238Z digest=sha256:9ecd2b8eb4edcd35d73a3135bbbfa24ad742c39eef9d71fe535330dac164c7e0

Observation 17bf2fa9-832a-4d4e-b810-02226b751b2b · inbound

Perceive-to-Reason: Decoupling Perception and Reasoning for Fine-Grained Visual Reasoning cites this paper.

Perceive-to-Reason: Decoupling Perception and Reasoning for Fine-Grained Visual Reasoning PyVision: Agentic Vision with Dynamic Tooling

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-07-02T13:26:58.497512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-02T13:24:17.538850Z digest=sha256:3297580b6553b78c983642ecac8e8240c69079826c757bd43b06229d74cb5076

Observation 90cd6298-e4a7-4061-9495-76b0817be375 · inbound

CanvasAgent: Enabling Complex Image Creation and Editing via Visual Tool Orchestration cites this paper.

CanvasAgent: Enabling Complex Image Creation and Editing via Visual Tool Orchestration PyVision: Agentic Vision with Dynamic Tooling

Reference 35

Resolution
unresolved
no resolver link, observed 2026-07-11T15:24:53.016199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T15:24:53.016199Z digest=sha256:893033e70600d3f54d69bd0c657dc40d4b21d61dd5a33439d3080ab4f1a83ac3

Observation c0b2f9e1-cf90-44e3-8f8d-2e6eee964a40 · inbound

VC-Tooler: Learning Compositional and Adaptive Visual Tool Use cites this paper.

VC-Tooler: Learning Compositional and Adaptive Visual Tool Use PyVision: Agentic Vision with Dynamic Tooling

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T11:21:33.020557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T11:21:33.020557Z digest=sha256:9437c231c4f08b1b8fb9bf2f253e9e0a25781120740021fc7f03fb053e774e64

Observation cd061875-bfeb-490f-819e-a5db4e0e4a42 · inbound

InSight-doc: Agentic Visual Perception for Long-Document Understanding cites this paper.

InSight-doc: Agentic Visual Perception for Long-Document Understanding PyVision: Agentic Vision with Dynamic Tooling

Reference 138

Resolution
unresolved
no resolver link, observed 2026-08-12T20:43:53.033370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:43:53.033370Z digest=sha256:efb845d26b476abfa6b4dd9fb2f331b6803e0581233a45c5dff2a885a4a58506

Observation b20e04b2-c8af-4885-aab2-9b3f0944e60b · inbound

Advancing MLLM-based UAV Image Understanding and Reasoning: A Benchmark and a Training-Free Multi-Agent System cites this paper.

Advancing MLLM-based UAV Image Understanding and Reasoning: A Benchmark and a Training-Free Multi-Agent System PyVision: Agentic Vision with Dynamic Tooling

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T00:31:27.386319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:27.386319Z digest=sha256:58bd4ecb2184a8382c4defd082900e0f45316cd52293792727acd8badf1ef670