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Paper Citation Record · LEDGER

Grounding Computer Use Agents on Human Demonstrations

As of 5 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 2 inbound Pith citation observations for arXiv:2511.07332.

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

pith.paper-citation-record.v1
2511.07332 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T23:06:05.164684Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:04:30.614443Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

58 of 58 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved57
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

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

Outbound references

Observation db5a663d-829b-4f40-b22a-24782d24299c · outbound

This paper cites Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs.

Grounding Computer Use Agents on Human Demonstrations Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs

Reference 1

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source=arxiv_source observed=2026-08-03T23:06:03.723162Z digest=sha256:c45dfcfb8307831c429fb07518a4587cdc40fc94657b3f66306535ced943d83b

Observation f6f83e6d-f09c-4f7d-b5e1-01fea13b3fd8 · outbound

This paper cites Introducing computer use, a new claude 3.5 sonnet, and claude 3.5 haiku, October 2024 a.

Grounding Computer Use Agents on Human Demonstrations Introducing computer use, a new claude 3.5 sonnet, and claude 3.5 haiku, October 2024 a

Reference 2

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source=arxiv_source observed=2026-08-03T23:06:03.759451Z digest=sha256:4d7ca40e1262ef7b879f67a89fb1c72ef8db8e1f36c20c1bf0f7837c628948b2

Observation 1a890876-d950-40c1-8e62-1c79b5f0bce4 · outbound

This paper cites Introducing claude 4, May 2025 a.

Grounding Computer Use Agents on Human Demonstrations Introducing claude 4, May 2025 a

Reference 3

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source=arxiv_source observed=2026-08-03T23:06:03.869268Z digest=sha256:05acaa776d68baca7a83d6e9c219553b83d6a9b033b74b01896f92da135d575c

Observation 4517e066-3db1-4a29-abfa-ed3d3a2cb897 · outbound

This paper cites Introducing claude sonnet 4.5, September 2025 b.

Grounding Computer Use Agents on Human Demonstrations Introducing claude sonnet 4.5, September 2025 b

Reference 4

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source=arxiv_source observed=2026-08-03T23:06:03.927242Z digest=sha256:8df6e5d043be1a495bef1e74ba33b19602a965da263374130e3b02b6f8bc2fca

Observation d88d38fe-c582-4889-92a4-239dd373f2dc · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku.

Grounding Computer Use Agents on Human Demonstrations The claude 3 model family: Opus, sonnet, haiku

Reference 5

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source=arxiv_source observed=2026-08-03T23:06:04.010505Z digest=sha256:254c0636a3600fcf923ded6da2340b2a95aa887440bbcf6e875a04fe79616a4a

Observation ee618a87-2480-41c5-9e2f-0d8e6d64ca0a · outbound

This paper cites UIBert: Learning Generic Multimodal Representations for UI Understanding.

Grounding Computer Use Agents on Human Demonstrations UIBert: Learning Generic Multimodal Representations for UI Understanding

Reference 6

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source=arxiv_source observed=2026-08-03T23:06:04.092873Z digest=sha256:c8cf0f93bb851fd8492ec0ef5784bffe740a2d5358939065b469e04de1ab9b42

Observation 132eac72-4afd-49c9-849e-02e1508e1fb8 · outbound

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

Grounding Computer Use Agents on Human Demonstrations Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 7

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source=arxiv_source observed=2026-08-03T23:06:04.189598Z digest=sha256:e56519a7e20941a62f49700fe41ab5f5755ec05d73b684aef4fa860a12c5e10d

Observation fb6fef7d-4d64-4185-a415-fed91fdece0c · outbound

This paper cites Qwen2.5-VL Technical Report.

Grounding Computer Use Agents on Human Demonstrations Qwen2.5-VL Technical Report

Reference 8

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source=arxiv_source observed=2026-08-03T23:06:04.271966Z digest=sha256:3a0074119da2a9d7867116dd481cb207b88e5f1608a5c1498959f6a1e149fe06

Observation 0af08ad0-7566-4f86-9c1d-f4c834d7ba6c · outbound

This paper cites AMEX: Android Multi-annotation Expo Dataset for Mobile GUI Agents.

Grounding Computer Use Agents on Human Demonstrations AMEX: Android Multi-annotation Expo Dataset for Mobile GUI Agents

Reference 9

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source=arxiv_source observed=2026-08-03T23:06:04.431774Z digest=sha256:34073ea3a88efbb89633b393f919f5b053d01937f0158a1352989aa2c3bd01ad

Observation b1624e81-117c-4a57-a075-11c4bff191bd · outbound

This paper cites GUICourse: From General Vision Language Models to Versatile GUI Agents.

Grounding Computer Use Agents on Human Demonstrations GUICourse: From General Vision Language Models to Versatile GUI Agents

Reference 10

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source=arxiv_source observed=2026-08-03T23:06:04.595637Z digest=sha256:8c60eb50e0f2c0e6b3dca9a8e5dd0d2d9f5276548ee25254c58b2d2d7d5704e8

Observation 3c539971-c60d-419d-9ee3-6b1807e9002f · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Grounding Computer Use Agents on Human Demonstrations Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 11

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source=arxiv_source observed=2026-08-03T23:06:04.647028Z digest=sha256:cc98f0f2b12cd40b780350b18551524cf881230c280514d8519d3b5d1dc1baed

Observation 07e05dca-9399-4ebc-98dd-4353d91f9d77 · outbound

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

Grounding Computer Use Agents on Human Demonstrations SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents

Reference 12

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source=arxiv_source observed=2026-08-03T23:06:04.772053Z digest=sha256:a947718b30283d9f47beeea9b80a0f93d298617d5820e4ad515a53b29d456f3d

Observation 8c19df76-e218-4b39-92bd-e4179ff26e7a · outbound

This paper cites PaddleOCR 3.0 Technical Report.

Grounding Computer Use Agents on Human Demonstrations PaddleOCR 3.0 Technical Report

Reference 13

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source=arxiv_source observed=2026-08-03T23:06:04.793443Z digest=sha256:8055842684ee88e6fea51dd9d69b4991e83549db6881a24f261a3903063f5bc8

Observation 80cb7af6-73d2-4308-bb1f-272446823607 · outbound

This paper cites Rico: A mobile app dataset for building data-driven design applications.

Grounding Computer Use Agents on Human Demonstrations Rico: A mobile app dataset for building data-driven design applications

Reference 14

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source=arxiv_source observed=2026-08-03T23:06:04.835184Z digest=sha256:3e8f1890fa3b24e0b65ecd7a2ef2e22f70d7fac2a9bf06db02fda86afa95f4e8

Observation 7a6a37c1-697a-44e6-a321-fbc5b1846e61 · outbound

This paper cites PairBench: Are Vision-Language Models Reliable at Comparing What They See?.

Grounding Computer Use Agents on Human Demonstrations PairBench: Are Vision-Language Models Reliable at Comparing What They See?

Reference 15

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source=arxiv_source observed=2026-08-03T23:06:04.855888Z digest=sha256:9b2005502122ad913e88e6a3d5a3b747165dbb98a691bce5b77b6db840841ff0

Observation 64e65654-9c14-4ad2-9ca1-f2ce6c155e36 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Grounding Computer Use Agents on Human Demonstrations Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 16

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source=arxiv_source observed=2026-08-03T23:06:04.860471Z digest=sha256:7a2759a78a64a589e8596afb1ccaca330b74eb271ab3e0fc676015b5be7ed9e0

Observation a68ee014-a1ed-4347-9653-66f0c360157a · outbound

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

Grounding Computer Use Agents on Human Demonstrations Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents

Reference 18

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source=arxiv_source observed=2026-08-03T23:06:04.872520Z digest=sha256:0d5de7ffc9c5d069d59473f6ca9ba616dc1e04feeb0317c1adfb41783eb6c6a3

Observation 541baa7e-2523-43be-b12a-811fa3045d01 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Grounding Computer Use Agents on Human Demonstrations DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 19

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source=arxiv_source observed=2026-08-03T23:06:04.877333Z digest=sha256:a6d3466b3a944e0f002edc478b0f98561484e69322bd3e03b16ef0e9c74c3e8d

Observation 3be052ac-8eed-4fad-9a52-bf977b2ebc20 · outbound

This paper cites CogAgent: A Visual Language Model for GUI Agents.

Grounding Computer Use Agents on Human Demonstrations CogAgent: A Visual Language Model for GUI Agents

Reference 20

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source=arxiv_source observed=2026-08-03T23:06:04.882108Z digest=sha256:00fda70c95d9297d31e5fa47efb8d9678c57c739f0d131d92ffad248b2a7aed4

Observation ebf26015-b100-4edf-b917-5bb22bcb914e · outbound

This paper cites Kimi-VL Technical Report.

Grounding Computer Use Agents on Human Demonstrations Kimi-VL Technical Report

Reference 21

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source=arxiv_source observed=2026-08-03T23:06:04.886225Z digest=sha256:19074f2557b11c6ac8654a034029f0e786e6e827afd5f72ef0e4fcfbb5988f34

Observation 2692efef-be89-4840-95c6-d25f1c5877a0 · outbound

This paper cites Screenspot-pro: Gui grounding for professional high-resolution computer use, 2025.

Grounding Computer Use Agents on Human Demonstrations Screenspot-pro: Gui grounding for professional high-resolution computer use, 2025

Reference 22

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source=arxiv_source observed=2026-08-03T23:06:04.890498Z digest=sha256:5f00502efc9dcfc1362d96b018c5e4e29776529aac5f1e023724105ff473301a

Observation 145bd27c-b809-44c4-8ae2-eed3d721b7fc · outbound

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

Grounding Computer Use Agents on Human Demonstrations Mapping Natural Language Instructions to Mobile UI Action Sequences

Reference 23

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source=arxiv_source observed=2026-08-03T23:06:04.894273Z digest=sha256:467fe258c4ab3d1912b2f689250953889a024a2eadbcf580a6d5123b12643142

Observation fc2bc87a-0c3b-4c8c-928e-c3c69892ab03 · outbound

This paper cites Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements.

Grounding Computer Use Agents on Human Demonstrations Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements

Reference 24

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source=arxiv_source observed=2026-08-03T23:06:04.899120Z digest=sha256:8207667f144fafb7e966124ea6cc6aebc21acf1593e196684e8a2fe09ca8bd0c

Observation 8a3e9fe5-f353-494a-8a6d-e3914f42405a · outbound

This paper cites ShowUI: One Vision-Language-Action Model for GUI Visual Agent.

Grounding Computer Use Agents on Human Demonstrations ShowUI: One Vision-Language-Action Model for GUI Visual Agent

Reference 25

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source=arxiv_source observed=2026-08-03T23:06:04.903445Z digest=sha256:199205c11720447d8d1e3191b23b434c700f687c766d6759f54b3b756724c38c

Observation 41cf2645-2615-4ebf-9596-a599a9925136 · outbound

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

Grounding Computer Use Agents on Human Demonstrations InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners

Reference 26

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source=arxiv_source observed=2026-08-03T23:06:05.022849Z digest=sha256:13875bd9d055574b6808d6b4dac315b5f4a6692a3df738b9d554e7bc92bb9823

Observation d4e603f6-a477-48cd-8a4b-42d5bb6f4cf0 · outbound

This paper cites Infigui-g1: Advancing gui grounding with adaptive exploration policy optimization, 2025 b.

Grounding Computer Use Agents on Human Demonstrations Infigui-g1: Advancing gui grounding with adaptive exploration policy optimization, 2025 b

Reference 27

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source=arxiv_source observed=2026-08-03T23:06:05.027595Z digest=sha256:2fb6e45c010d8d2f4b9bf3960dc73e60962db5858e3055d0bf0e7d19ced46f18

Observation 3903365b-e94f-48ea-8b1b-8fdcf5098803 · outbound

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

Grounding Computer Use Agents on Human Demonstrations UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning

Reference 28

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source=arxiv_source observed=2026-08-03T23:06:05.031828Z digest=sha256:57e77f82560b9ddae714b5e3fd1ab6e13df0aae9b889468b14ed4fa19f3c6633

Observation f56f0e0c-91d1-4670-8df5-b3bed901b4a7 · outbound

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

Grounding Computer Use Agents on Human Demonstrations GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents

Reference 29

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source=arxiv_source observed=2026-08-03T23:06:05.036856Z digest=sha256:09407b315daa17ece5f5d8330d1ba6ff48d428140197951b88e5376654cd1026

Observation 30082b38-2f76-44ba-b9f6-4e9faa5e01b8 · outbound

This paper cites Pal, and Siva Reddy.

Grounding Computer Use Agents on Human Demonstrations Pal, and Siva Reddy

Reference 30

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source=arxiv_source observed=2026-08-03T23:06:05.041552Z digest=sha256:623f6cbf25f0e96ebbf7b0b5f7e3a71ccfdbff945365c0a439845d6546051ae7

Observation 2f80533e-f05e-426c-b962-8a034b3f1312 · outbound

This paper cites Screen2AX: Vision-Based Approach for Automatic macOS Accessibility Generation.

Grounding Computer Use Agents on Human Demonstrations Screen2AX: Vision-Based Approach for Automatic macOS Accessibility Generation

Reference 31

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source=arxiv_source observed=2026-08-03T23:06:05.045839Z digest=sha256:d6ba1a249c5790492368c6166e60126593c0afbadb3157dcda74d4670568ed17

Observation 19cc78c7-807a-4275-a56d-bbaea56c9179 · outbound

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

Grounding Computer Use Agents on Human Demonstrations UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction

Reference 32

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source=arxiv_source observed=2026-08-03T23:06:05.050263Z digest=sha256:6e23c98dc00b28b4f614a757b029d26772c257d95dfa8174c8768f8d5808406e

Observation a946bda3-a81d-48f8-b7b7-a23e294bfc93 · outbound

This paper cites Gpt-4 technical report, 2023.

Grounding Computer Use Agents on Human Demonstrations Gpt-4 technical report, 2023

Reference 33

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source=arxiv_source observed=2026-08-03T23:06:05.054640Z digest=sha256:0bc09dc1d8c09eb640f372fa6ab944b0a49bf560afe8c6f57963013e60ffcd5b

Observation abaf55fa-aca8-440b-a07f-ec7cf4df51f9 · outbound

This paper cites Hello gpt-4o, May 2024.

Grounding Computer Use Agents on Human Demonstrations Hello gpt-4o, May 2024

Reference 34

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source=arxiv_source observed=2026-08-03T23:06:05.058756Z digest=sha256:b05f582e56423fdd9d0e9dd29aab88e1b5597788bf66a0f59af891ad77791655

Observation 9d0216bb-325a-45fc-8595-26832b4d0f08 · outbound

This paper cites Introducing openai o3 and o4-mini, April 2025.

Grounding Computer Use Agents on Human Demonstrations Introducing openai o3 and o4-mini, April 2025

Reference 35

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source=arxiv_source observed=2026-08-03T23:06:05.062690Z digest=sha256:459ff9ff7b2a9bcf0c201fe0eb790c49b1897b41c13e32d1291ba8c2629577fe

Observation 3cb7f3d3-942c-470f-92b2-0f1f51a12124 · outbound

This paper cites Computer-using agent, January 2025.

Grounding Computer Use Agents on Human Demonstrations Computer-using agent, January 2025

Reference 36

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source=arxiv_source observed=2026-08-03T23:06:05.066497Z digest=sha256:26a5729cd249e681009d7733165355f093b9c69ab1e5b9d9ac4c3da83fa3f61a

Observation 0ad4ff3b-1f4e-47fa-a4e1-cc54372d4bf7 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

Grounding Computer Use Agents on Human Demonstrations The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 37

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source=arxiv_source observed=2026-08-03T23:06:05.070454Z digest=sha256:1358aa44ea98f4d2147abccb023a84652e27ccc0e4950b1a82436b5c1ae275ef

Observation 1a55f357-d574-4b01-8254-feb21b05de15 · outbound

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

Grounding Computer Use Agents on Human Demonstrations UI-TARS: Pioneering Automated GUI Interaction with Native Agents

Reference 38

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source=arxiv_source observed=2026-08-03T23:06:05.074681Z digest=sha256:8a07b96acd4ac925ef91853803dd0c1bcbc9ccb4e75a171c87cc1db9f512c8c6

Observation f6c0b410-afb4-4c13-b8d2-ab2e4e955358 · outbound

This paper cites Seed1.5-vl technical report, 2025.

Grounding Computer Use Agents on Human Demonstrations Seed1.5-vl technical report, 2025

Reference 39

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source=arxiv_source observed=2026-08-03T23:06:05.079123Z digest=sha256:d3e35331b8630c28720f9225cc0ce92ab3ee6f5853884437e00d12daea69dc4c

Observation 4fe4186c-0dfd-4355-9368-bcb0d02d2150 · outbound

This paper cites GUI-G$^2$: Gaussian Reward Modeling for GUI Grounding.

Grounding Computer Use Agents on Human Demonstrations GUI-G$^2$: Gaussian Reward Modeling for GUI Grounding

Reference 40

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source=arxiv_source observed=2026-08-03T23:06:05.083240Z digest=sha256:0d147cdfe32adcd5430eb8a3f734f9dcc755f5e51d7f39838e4f4799e7cae34d

Observation 791cfe7f-1392-4c58-92dc-99985ed7c900 · outbound

This paper cites Charles, Zhilin Yang, and Tao Yu.

Grounding Computer Use Agents on Human Demonstrations Charles, Zhilin Yang, and Tao Yu

Reference 41

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no resolver link, observed 2026-08-03T23:06:05.087509Z

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source=arxiv_source observed=2026-08-03T23:06:05.087509Z digest=sha256:20ced155317c2932de69c2b6b765a828a5e1964b2eb3919add2e2e4e2455864e

Observation c0785da3-2323-4630-8062-c38256276b9d · outbound

This paper cites MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents.

Grounding Computer Use Agents on Human Demonstrations MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents

Reference 42

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source=arxiv_source observed=2026-08-03T23:06:05.091486Z digest=sha256:b582381333a9026a9e63fe33e228ca35d743bf5b6e2e402b3be5992c13d6f54a

Observation cc67adb0-ad3d-45cf-9032-84a7d0066d70 · outbound

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

Grounding Computer Use Agents on Human Demonstrations GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents

Reference 43

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source=arxiv_source observed=2026-08-03T23:06:05.095782Z digest=sha256:276a0c7f98e54457ed929de50c592d77f867c00852d622903b96cea1904280c1

Observation 9ad885b0-98c4-4a70-a2a0-ab4e74b19529 · outbound

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

Grounding Computer Use Agents on Human Demonstrations OS-ATLAS: A Foundation Action Model for Generalist GUI Agents

Reference 44

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source=arxiv_source observed=2026-08-03T23:06:05.100005Z digest=sha256:9e0eb43fbc1bf32de19871b94a87199b8bac6ebdf25cf64adf57d6eaf0bb3cc4

Observation c241e984-48ee-48d1-a161-aac21fd5e5aa · outbound

This paper cites Scaling computer-use grounding via user interface decomposition and synthesis.

Grounding Computer Use Agents on Human Demonstrations Scaling computer-use grounding via user interface decomposition and synthesis

Reference 45

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source=arxiv_source observed=2026-08-03T23:06:05.104304Z digest=sha256:d9f7412821914b9d56413d4dbe4b4cd5f27ff88a2e81ea259501f7b132285ca6

Observation 252f6a0b-9823-4e5e-8632-07d32cdee3da · outbound

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

Grounding Computer Use Agents on Human Demonstrations Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction

Reference 46

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no resolver link, observed 2026-08-03T23:06:05.108292Z

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source=arxiv_source observed=2026-08-03T23:06:05.108292Z digest=sha256:1885d01f46e5ac938d21cb29334d3c88cf76efc1734a924dc4d1f94dc68d81e2

Observation 904c39ff-6d7e-4fcf-9d71-04a9d42b3b3f · outbound

This paper cites GTA1: GUI Test-time Scaling Agent.

Grounding Computer Use Agents on Human Demonstrations GTA1: GUI Test-time Scaling Agent

Reference 47

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source=arxiv_source observed=2026-08-03T23:06:05.112420Z digest=sha256:17eb1155831410b7d486f1305fb3e2189c66b451e837df1772f42377034094a5

Observation 2a0d68fa-d289-42b3-9585-00ff73872133 · outbound

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

Grounding Computer Use Agents on Human Demonstrations Aria-UI: Visual Grounding for GUI Instructions

Reference 48

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source=arxiv_source observed=2026-08-03T23:06:05.116719Z digest=sha256:070a4e3145d9aa3710e859611da000ed639f37db5fc1dde3f754a14cbbdee3b8

Observation 39c88373-ecef-4384-98b7-96ae28f2ae29 · outbound

This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

Grounding Computer Use Agents on Human Demonstrations MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 49

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source=arxiv_source observed=2026-08-03T23:06:05.120893Z digest=sha256:fb833cc41d12c2c47f58fcf413c897979032cd1e3aced252764bb23f6b970069

Observation 43c2731b-eb06-4e20-a0df-05925fa0582c · outbound

This paper cites Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs.

Grounding Computer Use Agents on Human Demonstrations Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs

Reference 50

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source=arxiv_source observed=2026-08-03T23:06:05.125194Z digest=sha256:4f41a805442c7000b54ab775c5531cba593c5e2bbd765ed8653b328b1f25cbf1

Observation 07994362-2fc5-4b60-b1d0-aa5f8acc1588 · outbound

This paper cites Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning.

Grounding Computer Use Agents on Human Demonstrations Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning

Reference 51

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source=arxiv_source observed=2026-08-03T23:06:05.129224Z digest=sha256:e3a1f0e82fe253bdec36a3153fb53cfb9b65cc595f0f3e788b81f44214aaf21e

Observation 83416878-8c17-4644-ada6-24ba4e533c2e · outbound

This paper cites Phi-Ground Tech Report: Advancing Perception in GUI Grounding.

Grounding Computer Use Agents on Human Demonstrations Phi-Ground Tech Report: Advancing Perception in GUI Grounding

Reference 52

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source=arxiv_source observed=2026-08-03T23:06:05.133513Z digest=sha256:b753747b34d31f49a1ccae1ec3e365d5877de7f4a530d2882398be4630917b06

Observation cd9c8c1f-38ca-4cd2-9a4a-137237691b3a · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Grounding Computer Use Agents on Human Demonstrations LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 53

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source=arxiv_source observed=2026-08-03T23:06:05.137899Z digest=sha256:8c264877e5f17c822725c32d0608fd28752764a4f14d188c62848572a277590a

Observation c9a8f360-cb59-4cab-aaf8-d1ec47701775 · outbound

This paper cites GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents.

Grounding Computer Use Agents on Human Demonstrations GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents

Reference 54

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source=arxiv_source observed=2026-08-03T23:06:05.142213Z digest=sha256:adf8fba1ee8c9a31ae17067ed80658b9859eca33ae51195a349889d38d1a4394

Observation 1fca5f60-7a81-410f-ac06-9d137edd8d6f · outbound

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

Grounding Computer Use Agents on Human Demonstrations InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 55

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source=arxiv_source observed=2026-08-03T23:06:05.146662Z digest=sha256:c7eccb1770961d0ad19a1a4b1e446501d2bedd0c24caeb946badc282270fcbc1

Observation b09a5f94-b983-40bf-86fe-bd62549ecc16 · outbound

This paper cites write newline.

Grounding Computer Use Agents on Human Demonstrations write newline

Reference 56

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no resolver link, observed 2026-08-03T23:06:05.150794Z

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source=arxiv_source observed=2026-08-03T23:06:05.150794Z digest=sha256:1d3bfda9d3fc36d5b89563402a659ab2779e9f24cad20bd999434eb2ba42e3a2

Observation e22b0bbf-a435-436b-8203-d48599c18a41 · outbound

This paper cites @esa (Ref.

Grounding Computer Use Agents on Human Demonstrations @esa (Ref

Reference 57

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source=arxiv_source observed=2026-08-03T23:06:05.155526Z digest=sha256:e8062184e0764ba0bd6be9562d1d785a910e05b04b3b8dfa08f90b7dc44306bf

Observation f5577c75-d9df-4344-8cf6-5626123e8a0d · outbound

This paper cites an unresolved cited work.

Grounding Computer Use Agents on Human Demonstrations Unresolved cited work

Reference 58

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source=arxiv_source observed=2026-08-03T23:06:05.160524Z digest=sha256:44d36f3656464e914e72cea7523bf4bba548cf5d480a314335238abeada4e806

Observation 12afe2a4-83dc-459a-a2e0-5afe3c166f55 · outbound

This paper cites OK/Cancel.

Grounding Computer Use Agents on Human Demonstrations OK/Cancel

Reference 59

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malformed identifier
no resolver link, observed 2026-08-03T23:06:05.164684Z

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source=arxiv_source observed=2026-08-03T23:06:05.164684Z digest=sha256:ff434504427cedace1d3bd102e98321e773adb1d5984bd5a00c758a74d2a8261

Pith citing papers

Observation 0ec72790-d788-4785-b7e1-45667519951c · inbound

Learning from Failure: Inference-Time Self-Improvement for Computer-Use Agents cites this paper.

Learning from Failure: Inference-Time Self-Improvement for Computer-Use Agents Grounding Computer Use Agents on Human Demonstrations

Reference 5

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metadata mismatch
local_arxiv, observed 2026-07-01T06:25:27.077201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-07-01T06:17:02.089012Z digest=sha256:f00c7b4952ba0c1dc6bc2e66cd8c67f1dab845f181a8b562044c45e4766b762c

Observation 04b2f6fd-ea41-4d62-8fea-e1e615b64cad · inbound

Scaling GUI Agents with Visual State Transitions cites this paper.

Scaling GUI Agents with Visual State Transitions Grounding Computer Use Agents on Human Demonstrations

Reference 8

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no resolver link, observed 2026-07-31T23:04:30.614443Z

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source=pdf_text observed=2026-07-31T23:04:30.614443Z digest=sha256:cec52e8bd1634cd658061c80eb9a3e0b0bfaea8bf275f7eb022a945518b67345