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Paper Citation Record · LEDGER

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth?

As of 16 August 2026, this Paper Citation Record lists 100 of 120 outbound references and 4 inbound Pith citation observations for arXiv:2507.19132.

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

pith.paper-citation-record.v1
2507.19132 v1

Coverage vector

measured 100 of 120 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:05:09.433084Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:46:05.756917Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T07:14:21.231866Z

Reference resolution

100 of 120 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved98
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9c982985-1a39-41d7-a0f9-8f376f7d5305 · outbound

This paper cites Os agents: A survey on mllm-based agents for general computing devices use, 2024.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Os agents: A survey on mllm-based agents for general computing devices use, 2024

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.040905Z digest=sha256:4dc8d60e187ff19abe3b8df65e6c2cb82f8d80a02edd93688c084b1c00cd4a0e

Observation 42ea2da8-e791-41e0-a329-3e2c253cce5e · outbound

This paper cites The Dawn of GUI Agent: A Preliminary Case Study with Claude 3.5 Computer Use.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? The Dawn of GUI Agent: A Preliminary Case Study with Claude 3.5 Computer Use

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.045519Z digest=sha256:295516d01f528b5e063019c5d1edf44503baee91a080c96550976322c9c84832

Observation b1ac632e-1258-40a5-897a-bdbbef0ff07d · outbound

This paper cites Introducing operator.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Introducing operator

Reference 3

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source=pdf_text observed=2026-08-15T18:05:09.049988Z digest=sha256:e145e67c8640703a0ebe878e3aee0055e789f677550d6316c3e825acdc135fc6

Observation 262b78b6-cc14-4595-9326-1f8000e0c39c · outbound

This paper cites Claude 3.5 sonnet.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Claude 3.5 sonnet

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.057829Z digest=sha256:a225720b90dde08d23d173ccdf09e0a5a44a25cf34057146dc9e69eb2abdebd4

Observation 3f3c4583-8fc9-404d-a433-4a2ea459a535 · outbound

This paper cites UFO2: The Desktop AgentOS.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? UFO2: The Desktop AgentOS

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.061591Z digest=sha256:7be1cce2be3a7b6fd030dc86cb669b682dc0c97c8d7a7697e1b2bee9c7d4081c

Observation 4da7d4b9-67ec-4ca8-8f85-bdc385bf5ecc · outbound

This paper cites UI-TARS: Pioneering Automated GUI Interaction with Native Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? UI-TARS: Pioneering Automated GUI Interaction with Native Agents

Reference 6

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no resolver link, observed 2026-08-15T18:05:09.066201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.066201Z digest=sha256:b95efc82a4e3454b7b5c21a63329dc673a697d2056225991e89c94620291b8fb

Observation a3294bc6-9365-487f-b2b1-6f80038dbca0 · outbound

This paper cites OS-Copilot: Towards Generalist Computer Agents with Self-Improvement.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? OS-Copilot: Towards Generalist Computer Agents with Self-Improvement

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.070622Z digest=sha256:1655adf5e40cce9ce77172c445efbd5a0cc96bb0b75728d8608fd04c18b3a38c

Observation d010be63-dcd7-47f0-aea5-53f0d1444f35 · outbound

This paper cites Qwen2.5-VL Technical Report.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Qwen2.5-VL Technical Report

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.075272Z digest=sha256:3f8b141bc4f209b4ebc776bd3d3cff869c10731f0d121f3ba62f597b94a755bd

Observation e9f19549-555d-40ab-9e90-6259943e2d99 · outbound

This paper cites AutoGLM: Autonomous Foundation Agents for GUIs.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? AutoGLM: Autonomous Foundation Agents for GUIs

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.079162Z digest=sha256:218256b000444f5e6d1b6ab914d28acec5cea4f743f0ad542343045532299823

Observation 274488fe-947d-4a40-9548-e8de7c3abecb · outbound

This paper cites Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction

Reference 10

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no resolver link, observed 2026-08-15T18:05:09.082954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.082954Z digest=sha256:b69e61e9ba9f6a1a9ca620b2f23ee952247002339d5046ddc7f9412f01114b95

Observation 11a7e47a-eea6-42a1-993b-ebfa928631da · outbound

This paper cites OS-ATLAS: A Foundation Action Model for Generalist GUI Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? OS-ATLAS: A Foundation Action Model for Generalist GUI Agents

Reference 11

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no resolver link, observed 2026-08-15T18:05:09.086774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.086774Z digest=sha256:1dc184b4cbd466f76706bdeb8a2ab3c971553f0c7f04707a38a8378295e448c4

Observation 0b1b8c89-520b-47ea-8a1a-bff96307fe10 · outbound

This paper cites AppAgentX: Evolving GUI Agents as Proficient Smartphone Users.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? AppAgentX: Evolving GUI Agents as Proficient Smartphone Users

Reference 12

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no resolver link, observed 2026-08-15T18:05:09.091004Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.091004Z digest=sha256:f6b3501a8b83c74b1d679c05b7a1c81589167714c9de39337d2caa930ce47b5c

Observation 820d9e5f-4f73-4b99-b53b-97ada9e257c2 · outbound

This paper cites Agent S: An Open Agentic Framework that Uses Computers Like a Human.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Agent S: An Open Agentic Framework that Uses Computers Like a Human

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.094733Z digest=sha256:8501cc32ba2efcc5e30818cfbf34f628f63617a05ab6ee48d5a398ab8631a47c

Observation bd41e9ff-9347-46c6-8b5d-7190ccc5521d · outbound

This paper cites Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents

Reference 14

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.098379Z digest=sha256:a02204bb02b753cbea6ae92d26ea3ac9d90abe03b075075d96757235ff5984b3

Observation f5417553-3643-49d5-8123-2bd16279edb4 · outbound

This paper cites AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant

Reference 15

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no resolver link, observed 2026-08-15T18:05:09.101908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.101908Z digest=sha256:e896178e6cb216d0f7794a25f183b7ae49573310edfe0d7692e7cdfd569dec01

Observation 338a4d7f-0db4-4061-9817-454315b9f667 · outbound

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

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Mind2web: Towards a generalist agent for the web

Reference 16

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no resolver link, observed 2026-08-15T18:05:09.105560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.105560Z digest=sha256:4ccdd7ca67bc6cb742280e0184f16708e30e65052d4332af7713443a213c1ae4

Observation 765a1864-63b8-4a1c-bd28-1c519a0315e3 · outbound

This paper cites WebArena: A Realistic Web Environment for Building Autonomous Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? WebArena: A Realistic Web Environment for Building Autonomous Agents

Reference 17

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no resolver link, observed 2026-08-15T18:05:09.109177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.109177Z digest=sha256:4956d2cf1cf8f928acadbf4f9b37ecb383b0b9a65bd0c3fc347f2c00bcee8748

Observation d9aa38de-e5d9-4560-b81e-c1ef08fff11f · outbound

This paper cites Spider2-v: How far are multi- modal agents from automating data science and engineering workflows? Advances in Neural Information Processing Systems, 37:107703–107744, 2024.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Spider2-v: How far are multi- modal agents from automating data science and engineering workflows? Advances in Neural Information Processing Systems, 37:107703–107744, 2024

Reference 18

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no resolver link, observed 2026-08-15T18:05:09.112997Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.112997Z digest=sha256:b5e86e5bf9b7ac6c30aef0630b06bcba2590985e98140ae2ef3d8577642b96dd

Observation 7be98b53-3c32-4279-a6de-110df2c6d801 · outbound

This paper cites AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.116429Z digest=sha256:302b9c09e577307376ef5c34921ad8ff70a999ba600a36e685f81f541e80435b

Observation 83f8cb10-742d-4898-9d38-3f78826d7e37 · outbound

This paper cites WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.120167Z digest=sha256:e57af6427df6a8ed3745fc400c606a307cdb73476f4d33cd81ddd26689235c33

Observation 45537c06-898d-480f-86ba-8cc216162c94 · outbound

This paper cites Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments

Reference 21

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no resolver link, observed 2026-08-15T18:05:09.124004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.124004Z digest=sha256:a7571bc8e2f19dccee59600b7eedd09dcd6a249d9eddef7395e781b6a7895090

Observation 0221425f-af15-4612-9c25-610124af2164 · outbound

This paper cites Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale

Reference 22

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no resolver link, observed 2026-08-15T18:05:09.127680Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.127680Z digest=sha256:892a29a6a916087e05933c463adc9018066a8ffbc2f2a14753f9a9b0bff39f08

Observation b1a5d706-f8fd-4d26-98de-c7d15488edbf · outbound

This paper cites On the effects of data scale on ui control agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? On the effects of data scale on ui control agents

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.131571Z digest=sha256:cfd47c37aad9dc3bc9424bf76d9b521a5ade3df667b721b412cec90164eb1209

Observation f13d09b4-8647-43e4-a2e9-db85e1256011 · outbound

This paper cites Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles, April 2021.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles, April 2021

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.135605Z digest=sha256:a5d488e1d277b424d8e23fc3f9d4911ab02673c86b4828024e51fe9b99d233a9

Observation cff321d3-f8c5-4d1c-ab9a-0b634b6bb0be · outbound

This paper cites SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents

Reference 25

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no resolver link, observed 2026-08-15T18:05:09.139643Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.139643Z digest=sha256:317dc09131b8dca09a9d2f6a51ab5b8389bc454969202744420e91775946979a

Observation ec507c4f-f3fd-43f7-a57b-fcce7878816f · outbound

This paper cites Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents

Reference 26

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no resolver link, observed 2026-08-15T18:05:09.143507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.143507Z digest=sha256:b08c6fae2d75d56a39a9262db79c5e39f83963b1c760955440d5ed119f5d1bd1

Observation 57b5dc08-8224-4609-86c0-9f8e4551296f · outbound

This paper cites Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance

Reference 27

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no resolver link, observed 2026-08-15T18:05:09.147748Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.147748Z digest=sha256:421449aadc43ac71c130f3150fa68c7270397ef36096af764cfd5ace3d985953

Observation d8d96150-4537-4df8-af8a-74bfa40d8d14 · outbound

This paper cites Need help? designing proactive ai assistants for programming.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Need help? designing proactive ai assistants for programming

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.152152Z digest=sha256:32b81557f7ccfa34a4dd1deb6d750ff470de17c678838a2b316f09af9f977c25

Observation 5633c042-2459-4361-9e1e-c9829736a734 · outbound

This paper cites How should my chatbot interact? a survey on social characteristics in human–chatbot interaction design.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? How should my chatbot interact? a survey on social characteristics in human–chatbot interaction design

Reference 29

Resolution
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no resolver link, observed 2026-08-15T18:05:09.155653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.155653Z digest=sha256:69f001b092321d54345d2ebaa84065355b4ca2516c894d14e5fbdef9adf370d1

Observation 3b51e63b-18c9-43a4-bd9c-4ae0f5d7c89f · outbound

This paper cites Proactive conversational agents in the post-chatgpt world.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Proactive conversational agents in the post-chatgpt world

Reference 30

Resolution
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no resolver link, observed 2026-08-15T18:05:09.159207Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.159207Z digest=sha256:d3127003a28f791ba63b812017e6da474dcb2e798da19e59d2532ac3dd6dea6c

Observation 0678745c-f81b-4603-89fe-a238f9d5060c · outbound

This paper cites A3: Android agent arena for mobile gui agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? A3: Android agent arena for mobile gui agents

Reference 31

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no resolver link, observed 2026-08-15T18:05:09.162608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.162608Z digest=sha256:28b181e55eaf253c84e491a56e7858a071f819e65cc1249ca50762b09c268641

Observation fb76492d-9288-46de-bff3-902d35217f87 · outbound

This paper cites Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration

Reference 32

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no resolver link, observed 2026-08-15T18:05:09.166565Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.166565Z digest=sha256:bac3c9fe71cdfdd4eb9a9a53f49c56194b6aa152b7057047c6e5df5748c9e45b

Observation 9a4dc079-4dec-4422-817a-af77b213fe28 · outbound

This paper cites State of mobile 2025: The industry’s leading report.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? State of mobile 2025: The industry’s leading report

Reference 33

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no resolver link, observed 2026-08-15T18:05:09.170436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.170436Z digest=sha256:3b8abadeb7e75b9d723c66971dbb8fa186ad3b51e8cdccd191c28413589a7ed2

Observation b2da6331-fca2-469f-b340-e488f7055bc2 · outbound

This paper cites Ict access and usage database.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Ict access and usage database

Reference 34

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no resolver link, observed 2026-08-15T18:05:09.174541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.174541Z digest=sha256:1b90478f988ecb3d378932d617782c77b267ce969f73a0d328680378620d34d6

Observation 3b487486-47ac-42e4-abb8-0f4dbed5cd80 · outbound

This paper cites Position: Levels of agi for operationalizing progress on the path to agi.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Position: Levels of agi for operationalizing progress on the path to agi

Reference 35

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no resolver link, observed 2026-08-15T18:05:09.178314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.178314Z digest=sha256:15ce2b8a3342e6ff9bdcbb7a3e20801c6e8f414b4b98744f755d41a2b58dbea4

Observation fd5413c9-2b23-4f54-8c2b-1728fb030f29 · outbound

This paper cites Towards Building Specialized Generalist AI with System 1 and System 2 Fusion.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Towards Building Specialized Generalist AI with System 1 and System 2 Fusion

Reference 36

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no resolver link, observed 2026-08-15T18:05:09.182071Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.182071Z digest=sha256:5571807d10845caa0f85bc9037a2c22616d7be7ef1369d313941522bc5973c96

Observation 7f079565-9144-4f4f-9023-f30267b0c773 · outbound

This paper cites Gaia: a benchmark for general ai assistants.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Gaia: a benchmark for general ai assistants

Reference 37

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unresolved
no resolver link, observed 2026-08-15T18:05:09.186460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.186460Z digest=sha256:137752fa90807fcff3236f486744bdebaef6eda48d87d71c9ba3e920cb168779

Observation 66236df1-2121-4f88-a93e-a96863d2425e · outbound

This paper cites WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models

Reference 38

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source=pdf_text observed=2026-08-15T18:05:09.190120Z digest=sha256:a2e87ab269bcc33989396cd15b7318cdcda56ca85a68c6be2917f275b20e7847

Observation 05995c3f-b24e-4550-94ff-78ff96d500f1 · outbound

This paper cites Mapping Natural Language Instructions to Mobile UI Action Sequences.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Mapping Natural Language Instructions to Mobile UI Action Sequences

Reference 39

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source=pdf_text observed=2026-08-15T18:05:09.193824Z digest=sha256:de8c113ce2bbc70108fcfaf7ebd9a88c008b47319e574b227075a4ed6e30d54c

Observation bb8aca1a-9253-4546-be7f-ec0a0f6efe65 · outbound

This paper cites Omniact: A dataset and benchmark for enabling multimodal generalist autonomous agents for desktop and web.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Omniact: A dataset and benchmark for enabling multimodal generalist autonomous agents for desktop and web

Reference 40

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.197750Z digest=sha256:c7ae2fe578f220051346c6f37df2885f01cc194bb367a2929442096ac4f90695

Observation 7c1da0fc-915e-46f1-8913-a12ca98f383c · outbound

This paper cites Webshop: Towards scalable real-world web interaction with grounded language agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Webshop: Towards scalable real-world web interaction with grounded language agents

Reference 41

Resolution
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no resolver link, observed 2026-08-15T18:05:09.201407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.201407Z digest=sha256:96d3938e891a8ff7f5774be4fa5b3ecff5e9e212a0d43161fdb062af9bebf66b

Observation 05842f44-f960-46b7-a81a-768992360219 · outbound

This paper cites Understanding the weakness of large language model agents within a complex android environment.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Understanding the weakness of large language model agents within a complex android environment

Reference 42

Resolution
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no resolver link, observed 2026-08-15T18:05:09.204734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.204734Z digest=sha256:8f192cb6082642a99cd0f19c1bacd88d9dbbf9645c3d7341e9f2d3a785e1bf60

Observation 42f355e5-de0e-4b92-b0ab-fea0ab98468a · outbound

This paper cites TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Reference 43

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.208246Z digest=sha256:c363a01b711c4f929d82ee6a657fa282affe8df4655d44899087a8abf25a9912

Observation dd2dc19b-cc1e-4d91-bf3b-c33017ded1e2 · outbound

This paper cites ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows

Reference 44

Resolution
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no resolver link, observed 2026-08-15T18:05:09.212040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.212040Z digest=sha256:1c9cf0db52af87c57fbac3a96d64ebba4d23651eb2085809a71a6ac0c0848861

Observation 685e309d-352f-4364-bc0b-e3216cd9e3e8 · outbound

This paper cites GPT-4o System Card.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? GPT-4o System Card

Reference 45

Resolution
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no resolver link, observed 2026-08-15T18:05:09.216237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.216237Z digest=sha256:4d68e422713969d0832717b6e5859bb886c04bb9245c222aeb33aa9111159bbd

Observation 3a2390a4-2019-41c4-a695-269460e92159 · outbound

This paper cites Claude 3.7 sonnet.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Claude 3.7 sonnet

Reference 46

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.220134Z digest=sha256:c30f640c4bebd1583e9c5b68cd55de0f8399ca5ddf42e541dc7cdd679edc99a3

Observation ff8222b4-dc2a-4ce2-87e5-fba2425e123c · outbound

This paper cites Introducing gemini 2.0: our new ai model for the agentic era.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Introducing gemini 2.0: our new ai model for the agentic era

Reference 47

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.227736Z digest=sha256:02aa14612781111899c603ebaf81727b492e08a29fa56bcdb45f5f70950625ff

Observation b304899d-957c-4b06-a5dc-b412bf212930 · outbound

This paper cites an unresolved cited work.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Unresolved cited work

Reference 48

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parse uncertain
no resolver link, observed 2026-08-15T18:05:09.223913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.223913Z digest=sha256:03bbef1bf3135fc32eba718b03f502396ec989afe3ddd946c59a5b7aa4096389

Observation e6a431e5-0fd0-4921-9ef5-c579b5d73b5f · outbound

This paper cites GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents

Reference 49

Resolution
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no resolver link, observed 2026-08-15T18:05:09.235107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.235107Z digest=sha256:f6cc1b5a948774ab1e5ee1d8fc61fdacdc085749ab0e5665b92ece47fa129128

Observation fb4a3bb6-c689-4619-a303-1504ee466af9 · outbound

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

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 50

Resolution
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no resolver link, observed 2026-08-15T18:05:09.231076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.231076Z digest=sha256:e3e472bc171986476936154cfcde1a7f54418f842d2e5947149afb0430cc9e36

Observation fe98aa14-d7af-4f62-9753-88ebaa4b35c6 · outbound

This paper cites VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks

Reference 51

Resolution
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no resolver link, observed 2026-08-15T18:05:09.242842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.242842Z digest=sha256:8587741cd0c57f1436efc376a0dffc9a38f105ed15cd5e93836ea50a06e9d70d

Observation 7f8845d9-fdc8-48c2-86fb-cf9336e2fa49 · outbound

This paper cites A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond

Reference 52

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no resolver link, observed 2026-08-15T18:05:09.239167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.239167Z digest=sha256:d663e2475442e062011e7f003163d4a036347528412b41b742cdd29bf5ad307c

Observation cf71ac9c-007a-4074-9ebc-2bf59a010aaa · outbound

This paper cites An- droidinthewild: A large-scale dataset for android device control.Advances in Neural Information Processing Systems, 36:59708–59728, 2023.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? An- droidinthewild: A large-scale dataset for android device control.Advances in Neural Information Processing Systems, 36:59708–59728, 2023

Reference 53

Resolution
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no resolver link, observed 2026-08-15T18:05:09.249982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.249982Z digest=sha256:5efa74e5d57bae811542b7f4efdd153ecc5ac673b28bcec5ba0111de01c9974e

Observation af8737ca-a8eb-4f6f-adec-119ddcb46c29 · outbound

This paper cites VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.246375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.246375Z digest=sha256:e23398af9a248100fd033df2adf8f09fa974e6afe0a4261649a4eda3495a8955

Observation e425ef79-3fde-4605-8fa1-c7e91d30829c · outbound

This paper cites Gui-world: A dataset for gui-oriented multimodal llm-based agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Gui-world: A dataset for gui-oriented multimodal llm-based agents

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.257413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.257413Z digest=sha256:f11d0f7d865e4689bdc6979a9de27a95e40f15e3ca140198aa1842ee86734732

Observation 6128d8cd-e625-4614-aa6d-fdf8b752c9c8 · outbound

This paper cites GUIOdyssey: A Comprehensive Dataset for Cross-App GUI Navigation on Mobile Devices.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? GUIOdyssey: A Comprehensive Dataset for Cross-App GUI Navigation on Mobile Devices

Reference 56

Resolution
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no resolver link, observed 2026-08-15T18:05:09.253418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.253418Z digest=sha256:11f22380c222e0716e4ac2d85415b7f029fb45d9e3d4449af93272dfed8420d5

Observation dff0e536-da70-4683-93b7-90081448f080 · outbound

This paper cites ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.264839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.264839Z digest=sha256:514c47808af551a1c0a39808e2cb763287e2bf01199966cf99a711f0212e580c

Observation 955a4933-4c04-4c0b-b6a4-786b43b039ed · outbound

This paper cites Vision- language models can self-improve reasoning via reflection.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Vision- language models can self-improve reasoning via reflection

Reference 58

Resolution
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no resolver link, observed 2026-08-15T18:05:09.260872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.260872Z digest=sha256:e4f2b8624c1792edb581799a54e09f2279dc1e2927abc357bffe84d21642bb40

Observation 5f34805e-5575-4936-a1e1-290189356a0a · outbound

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

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Cogagent: A visual language model for gui agents

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.273053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.273053Z digest=sha256:a6979510565661bf6662d720ebed98472ccdf5ab5d8e16b4a8b721373137963f

Observation 8535f3e5-6523-4fd4-8a3c-6aa1c3318a5b · outbound

This paper cites UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction

Reference 60

Resolution
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no resolver link, observed 2026-08-15T18:05:09.268927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.268927Z digest=sha256:deb208dd87ee366d547ab9dcfd74e7e4733292e876957deb213cd8ff7702153c

Observation 67776c46-39b3-49ce-9e64-5b73dd049f04 · outbound

This paper cites Aria-UI: Visual Grounding for GUI Instructions.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Aria-UI: Visual Grounding for GUI Instructions

Reference 61

Resolution
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no resolver link, observed 2026-08-15T18:05:09.280476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.280476Z digest=sha256:ff30545cdbfa3b25a297f57461f31d08259a1f0e48e2a8631921f88b8d4b4aa6

Observation 8dbfc865-3ece-441c-8c84-acbd18e0ba2d · outbound

This paper cites Ferret-ui: Grounded mobile ui understanding with multimodal llms.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Ferret-ui: Grounded mobile ui understanding with multimodal llms

Reference 62

Resolution
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no resolver link, observed 2026-08-15T18:05:09.276794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.276794Z digest=sha256:88c9aeb9d76b718137c64bc79ce8a0f1b996c29e0523ed5ad3d7387d0c8ea7fc

Observation 3befbff8-0d15-4f3a-8a88-950c2955dd53 · outbound

This paper cites Iris: Breaking GUI Complexity with Adaptive Focus and Self-Refining.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Iris: Breaking GUI Complexity with Adaptive Focus and Self-Refining

Reference 63

Resolution
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no resolver link, observed 2026-08-15T18:05:09.289637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.289637Z digest=sha256:26f95f8a188f4a3a8bbf4d12b796e94c332bd465bb6553cb8a3d803bea8a6a30

Observation 85b7aaf0-a1f8-4afd-9e57-163ac26d642b · outbound

This paper cites Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms

Reference 64

Resolution
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no resolver link, observed 2026-08-15T18:05:09.284586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.284586Z digest=sha256:07b5a4759055e59c5bcb92c004d14bdb7a74271f2493dcf8095a45ebfc3b019c

Observation 9f1041f0-0d4b-4ec4-98ad-2bf7599cae42 · outbound

This paper cites Showui: One vision-language-action model for generalist gui agent.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Showui: One vision-language-action model for generalist gui agent

Reference 65

Resolution
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no resolver link, observed 2026-08-15T18:05:09.297440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.297440Z digest=sha256:bc39b9746481a890dd72b37e7810da984ded7f0d65fe03547f76a0360877c830

Observation 34e61441-4688-439b-81d2-04a67706db68 · outbound

This paper cites Ui-hawk: Unleashing the screen stream understanding for gui agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Ui-hawk: Unleashing the screen stream understanding for gui agents

Reference 66

Resolution
verified exact
raw_fallback, observed 2026-08-15T18:05:09.981402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:05:09.293763Z digest=sha256:cbac9224ebc2e98605e5713dfe383ae8d153e4a5bdae25de2a40856a15533f55

Observation 54489867-d679-4ce6-863a-775806b8c29f · outbound

This paper cites MobileVLM: A Vision-Language Model for Better Intra- and Inter-UI Understanding.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? MobileVLM: A Vision-Language Model for Better Intra- and Inter-UI Understanding

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.305960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.305960Z digest=sha256:6e74ea94105a915db50c0fef5c8b2f4b5d8e54a7ab5833130dc3b9cdba0cc896

Observation 9ca2e3cf-e92a-4340-a5cc-62130ccde8a2 · outbound

This paper cites EDGE: Enhanced Grounded GUI Understanding with Enriched Multi-Granularity Synthetic Data.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? EDGE: Enhanced Grounded GUI Understanding with Enriched Multi-Granularity Synthetic Data

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.301785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.301785Z digest=sha256:badcaacfc211d6b7d9cc4456b1e4094ac67f95248a5d08f6697c43f5d66de9d1

Observation 28d91fe2-762f-4d5c-92b5-d415fa9b3fca · outbound

This paper cites Mobileviews: A large-scale mobile gui dataset.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Mobileviews: A large-scale mobile gui dataset

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.314337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.314337Z digest=sha256:d47d2cd1163755ed9309278e83115f365db1b1b2f3fdc0ba21fd0abd6f7201bb

Observation 6cc33f35-e2bd-43c5-b7cd-28fa9a3c8268 · outbound

This paper cites OmniParser for Pure Vision Based GUI Agent.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? OmniParser for Pure Vision Based GUI Agent

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.310077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.310077Z digest=sha256:9082d0e1e0693fb33723593eca8cb1c55431a45e6e55b6054de84a1ab46276ed

Observation 0da24411-2915-4e71-a5b3-270983f2c4db · outbound

This paper cites Android in the Zoo: Chain-of-Action-Thought for GUI Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Android in the Zoo: Chain-of-Action-Thought for GUI Agents

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.322241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.322241Z digest=sha256:b071f544dfffe7c2a55e4eaead9dc4a869c93bf264466842bf3128ab5579c9c2

Observation 083ab7f0-c10e-414a-a14b-33d27c830257 · outbound

This paper cites Synatra: Turning Indirect Knowledge into Direct Demonstrations for Digital Agents at Scale.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Synatra: Turning Indirect Knowledge into Direct Demonstrations for Digital Agents at Scale

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.318171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.318171Z digest=sha256:02c80010c994e2e2fa06da1df51baf6f0697ece11b52d6638d97e4ba25707ee6

Observation 6afa31d2-109b-4e02-9364-04d8289f4cde · outbound

This paper cites Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.329862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.329862Z digest=sha256:cc160e70c84ad89e5c167722a870c1932cd310c0ac70df912a37b5c77ab5fb96

Observation dca6bc02-dbf0-4d74-999b-14b64c08040e · outbound

This paper cites OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-15T18:05:09.325944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:05:09.325944Z digest=sha256:a610256b1de0df16c479c88c2805c09423bb6e8add2e005724881f08910b1451

Observation 5cd0baff-79b0-4f3b-85fe-5688eaf22f2a · outbound

This paper cites AGILE: A Novel Reinforcement Learning Framework of LLM Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? AGILE: A Novel Reinforcement Learning Framework of LLM Agents

Reference 75

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source=pdf_text observed=2026-08-15T18:05:09.338173Z digest=sha256:b620a2ecd4049bcfc84f440d69a7a0a82b39045d11b4dfe0bf7903dc99dea3ba

Observation 8077a4e0-edea-446f-98f3-42ab380049e5 · outbound

This paper cites GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration

Reference 76

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source=pdf_text observed=2026-08-15T18:05:09.334139Z digest=sha256:b1108030bc47e7ed7e245f24406a4b352e63e8de8f1a3bc01e5d4c6f6fefc2e1

Observation 25925f65-3209-4701-9598-15f976fa1c29 · outbound

This paper cites WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning

Reference 77

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source=pdf_text observed=2026-08-15T18:05:09.345860Z digest=sha256:370ccc312794c97e48b86fd7f5e6ef8de788804bfffe2fc3e64cb81b337d548f

Observation 7b0ea5e0-4a00-4566-8b56-5553683b645a · outbound

This paper cites Autowebglm: A large language model- based web navigating agent.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Autowebglm: A large language model- based web navigating agent

Reference 78

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source=pdf_text observed=2026-08-15T18:05:09.341945Z digest=sha256:a0e03f3b613f06ff99855699530809e9735665eb05700bd4062df9c3b4416afe

Observation 56c194ee-c4a3-43de-b22f-32004080d7fa · outbound

This paper cites GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents

Reference 79

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source=pdf_text observed=2026-08-15T18:05:09.354205Z digest=sha256:700023ecc3f51047f0cfe7a199b52c83bff0768ab292b56334aa839891425531

Observation daee5d42-3609-428a-befd-efcca63ce503 · outbound

This paper cites UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning

Reference 80

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source=pdf_text observed=2026-08-15T18:05:09.350021Z digest=sha256:f43bcc8f14c6210f99f40af11e1400717a6f0803f9fa54330a590766a38eb23f

Observation 60a646b5-506b-440d-808a-acd0b188454c · outbound

This paper cites React: Synergizing reasoning and acting in language models.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? React: Synergizing reasoning and acting in language models

Reference 81

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source=pdf_text observed=2026-08-15T18:05:09.362315Z digest=sha256:bc60ec13446815e9479e6a80c4c533913dd98abc53812751885cd5ac404d4f8a

Observation f796f067-393b-4617-bc97-06384ec23036 · outbound

This paper cites InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners

Reference 82

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source=pdf_text observed=2026-08-15T18:05:09.357902Z digest=sha256:1b26e262b82b6de7e58446ebdf36b776502be108d846a2f508b85e215ebf87f6

Observation a761270a-e784-404c-9b47-430f05796f59 · outbound

This paper cites Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents

Reference 83

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source=pdf_text observed=2026-08-15T18:05:09.369885Z digest=sha256:fef770ae7b88a9fb39c89836f892836486ab778881143501be14495cb0e8f974

Observation 02774239-551e-4be7-8175-7e9f53f08cd9 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36:8634–8652, 2023.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36:8634–8652, 2023

Reference 84

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source=pdf_text observed=2026-08-15T18:05:09.366194Z digest=sha256:3e92fe937c028e375bba1f306c52259871b4e069a73bcd0d0cee53b351a3c417

Observation 1548db0d-c413-43e4-95b6-29a597403d49 · outbound

This paper cites GPT-4V(ision) is a Generalist Web Agent, if Grounded.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? GPT-4V(ision) is a Generalist Web Agent, if Grounded

Reference 85

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source=pdf_text observed=2026-08-15T18:05:09.377788Z digest=sha256:88d108e75d2813c1f23a061c18ac20fe8aa392cfd80fd52da5e334af7b93b407

Observation 96e532e2-4705-4d74-9ac2-58320978c024 · outbound

This paper cites Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems

Reference 86

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source=pdf_text observed=2026-08-15T18:05:09.373636Z digest=sha256:022ed928a7da8701a98321fe2544f34eea0d7755f811d66ee3607b140275c24d

Observation 6ff35f08-d3bb-421c-9797-b4246756d15f · outbound

This paper cites Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration

Reference 87

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source=pdf_text observed=2026-08-15T18:05:09.386377Z digest=sha256:b3a01925a87ca758856bcd17dbee475b22a76f3b46b424774574af9badba0063

Observation ff247e3a-947e-4305-99f7-76ab2a3caccf · outbound

This paper cites Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation

Reference 88

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source=pdf_text observed=2026-08-15T18:05:09.381932Z digest=sha256:a903d4cfad7ae502ad79ebc64fab331456cc7d8546ce49fbbe39f1c7f2dfffc7

Observation 940bf9ea-c579-4357-bb48-9f34324dcc7c · outbound

This paper cites Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks

Reference 89

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source=pdf_text observed=2026-08-15T18:05:09.394122Z digest=sha256:0e7c53ad34f411aa31b3a88cae0eefe26b496336e02006164ea97a766c9f7d89

Observation 0815684c-d1bd-4bde-9527-58a81193f935 · outbound

This paper cites Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration

Reference 90

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source=pdf_text observed=2026-08-15T18:05:09.390202Z digest=sha256:b955a38df27b82ec4901da96fff9a35947f2e9349dbb790e8b9c60bdd3cb5edc

Observation ffdd3c22-93e2-4ac1-93e4-038e177c1c22 · outbound

This paper cites Human-automation interaction.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Human-automation interaction

Reference 91

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source=pdf_text observed=2026-08-15T18:05:09.402154Z digest=sha256:e3d1bbe2b761306cc36c1b193e6ea11e3117a0a08f17cdf4f143007b6587eee2

Observation 01c2645a-9358-4502-9612-06059f6fdbd3 · outbound

This paper cites LearnAct: Few-Shot Mobile GUI Agent with a Unified Demonstration Benchmark.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? LearnAct: Few-Shot Mobile GUI Agent with a Unified Demonstration Benchmark

Reference 92

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source=pdf_text observed=2026-08-15T18:05:09.398123Z digest=sha256:63ddc16004d9446da0f2eac9a3013a081f756d35a9f3cb0cd0dad8095617e69d

Observation 56d4133b-e951-4bfb-8a31-d28d4f6b9b1a · outbound

This paper cites Artificial general intelligence: concept, state of the art, and future prospects.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Artificial general intelligence: concept, state of the art, and future prospects

Reference 93

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source=pdf_text observed=2026-08-15T18:05:09.409779Z digest=sha256:ffcb9fd4f36719edc309a6fd5df16f22d5fbb0a495059f8ef712682e4c47e983

Observation 08cd63c1-bf63-491d-a841-f561ee6eea10 · outbound

This paper cites A model for types and levels of human interaction with automation.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? A model for types and levels of human interaction with automation

Reference 94

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source=pdf_text observed=2026-08-15T18:05:09.405889Z digest=sha256:1a87eaf7b00afb049eefbd66872e337bf4e491f9aecd6dc10c86cf068ad8f709

Observation bdff623f-1302-4b8a-aebf-7e35c56a9987 · outbound

This paper cites Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

Reference 95

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source=pdf_text observed=2026-08-15T18:05:09.417605Z digest=sha256:8b369499e76062296f95a56a8ad6a56590578eea157f2a1af72aa0a6ca5baea8

Observation c5001e70-8cf9-4e97-b3af-251bfe0dae01 · outbound

This paper cites Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

Reference 96

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source=pdf_text observed=2026-08-15T18:05:09.413471Z digest=sha256:7cc0ba064352f5ab0d83fb359b775f85d5c90f9b58461107d5babeaf38b8ee48

Observation d246ea7c-7d6f-41ac-b4d0-d6f85520727c · outbound

This paper cites To ensure reproducibility, each task begins by loading a designated snapshot.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? To ensure reproducibility, each task begins by loading a designated snapshot

Reference 98

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source=pdf_text observed=2026-08-15T18:05:09.422088Z digest=sha256:ee2bc4413e982539ff4e24fa48ed0f5b2fa2437b99a470b93b28bd6624db1acc

Observation 57b5fc20-62da-4777-a035-5e92e4146152 · outbound

This paper cites Once initialized, the system enters the execution loop.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Once initialized, the system enters the execution loop

Reference 99

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source=pdf_text observed=2026-08-15T18:05:09.425806Z digest=sha256:94fa9883c755857fbb50178b4a48be92a443336a7a91c1bd0a5425a7cd7632d5

Observation d6e47bbc-e878-4ef7-9ced-f295404edfa1 · outbound

This paper cites For certain tasks, the final state after agent execution is not directly extractable.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? For certain tasks, the final state after agent execution is not directly extractable

Reference 100

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source=pdf_text observed=2026-08-15T18:05:09.429357Z digest=sha256:e9f993527cf91934b27fdf8cb83544a5aa51f2b6c507b8cd78f0c93e9f30829b

Observation 23ea5747-c4a7-4eb5-8fb2-6ec89cc17357 · outbound

This paper cites The VMC includes a set of state extraction functions designed to retrieve relevant information from the VM.

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? The VMC includes a set of state extraction functions designed to retrieve relevant information from the VM

Reference 101

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source=pdf_text observed=2026-08-15T18:05:09.433084Z digest=sha256:c1c82b9f6e5f99de9723b45225d144e9b613f0570463bd387d1490b870a224b1

Pith citing papers

Observation 82b02cfa-4174-4edd-b3b2-5b91704f10da · inbound

OS-Sentinel: Towards Safety-Enhanced Mobile GUI Agents via Hybrid Validation in Realistic Workflows cites this paper.

OS-Sentinel: Towards Safety-Enhanced Mobile GUI Agents via Hybrid Validation in Realistic Workflows OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth?

Reference 5

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source=arxiv_source observed=2026-08-15T15:46:05.756917Z digest=sha256:27b3c7587e58d16f2f6cbcb3fe6e9bccb2117035735aef2ee0e66794a773a70b

Observation 25e3866d-776e-44e4-bdfd-1f3c023d21d4 · inbound

OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks cites this paper.

OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth?

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:14:21.233820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-30T07:10:38.909339Z digest=sha256:f1c10bd52a67b311d6427ee5444ddd042ec6991df3a7f7be0b202194a340e9af

Observation 7fe9c669-600e-45bf-b472-8a2965677b4f · inbound

OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks cites this paper.

OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth?

Reference 9

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source=pdf_text observed=2026-07-15T10:24:53.345620Z digest=sha256:ce5f98cd1a747265d928d362389964ce93a40dd848591bb7f4574ca0f624df66

Observation 1535705b-2d8b-45b2-9893-b62b1256c7c5 · inbound

OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models cites this paper.

OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth?

Reference 12

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source=pdf_text observed=2026-07-31T02:18:01.622960Z digest=sha256:76721ef35635134386746fbb4163f96c7a8da96168d1c10ae169158091d36ef5