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Paper Citation Record · LEDGER

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2406.11896.

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

pith.paper-citation-record.v1
2406.11896 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:15:54.174164Z

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

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5f3e55d0-2209-4451-961a-3e69d2040b29 · inbound

Large Language Model-Brained GUI Agents: A Survey cites this paper.

Large Language Model-Brained GUI Agents: A Survey DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 272

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arxiv_id, observed 2026-05-19T11:08:27.886474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T11:08:27.472508Z digest=sha256:343082318748007f2219ba02a18715f48d21b5b5e374a169ff44622039531e95

Observation 57210eb1-0b26-4073-b9cd-de722e8ef3cd · inbound

Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone cites this paper.

Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2

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no resolver link, observed 2026-08-11T19:28:37.783068Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:28:37.783068Z digest=sha256:144bf4dcbc58c491e12cf158ade6782574322e5517c3b3ab05db40be1bc882b5

Observation 4b949169-7a03-4831-bd01-fd609d5540d5 · inbound

From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons cites this paper.

From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 4

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source=pdf_text observed=2026-08-11T17:55:13.165733Z digest=sha256:a3dc87ec51aceeaa8b3732274ebd7570766401d5beb0072fd3a00ed72b278ed8

Observation 9cfa9139-4f08-4b86-9c16-79600364b844 · inbound

AutoDroid-V2: Boosting SLM-based GUI Agents via Code Generation cites this paper.

AutoDroid-V2: Boosting SLM-based GUI Agents via Code Generation DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2

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no resolver link, observed 2026-08-11T05:06:48.845143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:06:48.845143Z digest=sha256:71208b6b17dd8abc0d29c39e3d3fd5b02b70e2b0cc69a2d923b9afee609377e3

Observation 3c600c5b-3e54-43f7-96d3-3ae9a1749549 · inbound

Reinforcement Learning for Long-Horizon Interactive LLM Agents cites this paper.

Reinforcement Learning for Long-Horizon Interactive LLM Agents DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 4

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no resolver link, observed 2026-08-09T14:56:00.187032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:56:00.187032Z digest=sha256:db96442dad5cd8eef9a4de76fd1a97c9c1999d6b5a43c4f8782b2c16eb1df439

Observation 6ed1e4c6-d607-41d1-8886-8b337aed2a91 · inbound

AppVLM: A Lightweight Vision Language Model for Online App Control cites this paper.

AppVLM: A Lightweight Vision Language Model for Online App Control DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 1

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no resolver link, observed 2026-08-08T15:37:54.519563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:37:54.519563Z digest=sha256:03ad3ebc21f2921f7e6ccb1513f0e9d0e78e22c987694e1ed14105fdd9e42fa5

Observation 940735a0-7fbc-4adb-a395-994715bfa4f0 · inbound

Advancing Autonomous VLM Agents via Variational Subgoal-Conditioned Reinforcement Learning cites this paper.

Advancing Autonomous VLM Agents via Variational Subgoal-Conditioned Reinforcement Learning DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 4

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no resolver link, observed 2026-08-08T11:25:49.090555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:25:49.090555Z digest=sha256:f0658c9d34c801a5c40191c3b511085e4966cf38a3449dc2d7f66bd978fa186c

Observation 1e4b7b4c-0a65-427d-8e12-9cf119621f80 · inbound

TRISHUL: Towards Region Identification and Screen Hierarchy Understanding for Large VLM based GUI Agents cites this paper.

TRISHUL: Towards Region Identification and Screen Hierarchy Understanding for Large VLM based GUI Agents DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2021

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no resolver link, observed 2026-08-08T06:01:31.581813Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T06:01:31.581813Z digest=sha256:d31045c9fe9b2028c1d8036b662351e7655eb41ec8418b3fec0f9935eb4b0e32

Observation d4454652-81f3-42e6-a2b3-9a537faf939f · inbound

Digi-Q: Learning Q-Value Functions for Training Device-Control Agents cites this paper.

Digi-Q: Learning Q-Value Functions for Training Device-Control Agents DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2024

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no resolver link, observed 2026-08-07T20:57:48.364438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:57:48.364438Z digest=sha256:b44e09d08d832e3bd9771f1128c5d015f7472a9d733b7b8e77e8d4f3c49b65d2

Observation 7ad6cb1e-f8ba-4bbc-93b3-c1624f9c133e · inbound

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks cites this paper.

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2

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verified exact
arxiv_id, observed 2026-05-17T21:32:18.576546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-17T21:32:18.491541Z digest=sha256:c2b577b458cb6010bbca5ac2423f9a751bda0b8dba8f65ff1ed83d9622d36b98

Observation a24d3dba-8d57-4d66-bd5f-55b8283841e2 · inbound

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems cites this paper.

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 131

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arxiv_id, observed 2026-05-22T21:42:10.964670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-22T21:39:49.832151Z digest=sha256:be90e2ad44cdec369884c2984f406d2e4870b1acc49503f56d2d27492b8125a6

Observation b7f11972-07a5-4403-8f9c-243c49403920 · inbound

Guiding VLM Agents with Process Rewards at Inference Time for GUI Navigation cites this paper.

Guiding VLM Agents with Process Rewards at Inference Time for GUI Navigation DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2024

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no resolver link, observed 2026-08-16T11:15:54.174164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:15:54.174164Z digest=sha256:54c7e3097cb614f26893d4a1191248ea21b70ad7eaa7db3cf1762a580787b2d8

Observation b77c1ff2-78d9-4eec-aab2-973b4900d4ae · inbound

AndroidGen: Building an Android Language Agent under Data Scarcity cites this paper.

AndroidGen: Building an Android Language Agent under Data Scarcity DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 6

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no resolver link, observed 2026-08-16T06:01:29.210107Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T06:01:29.210107Z digest=sha256:1b3c6452edd185c04b7ed595bda5a0f1b1f1d059013a39f2960bdc2af80c011b

Observation e7c33ebd-f11e-44f7-a256-d7d3f4bfdf96 · inbound

Self-Challenging Language Model Agents cites this paper.

Self-Challenging Language Model Agents DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2024

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no resolver link, observed 2026-08-07T11:40:11.634772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:40:11.634772Z digest=sha256:9e7ae3768fe7084a2a1a85579cdc09263608d3da99edc60235fcbb2a61946092

Observation e94ea10d-0614-4f9b-860c-ae435ececd19 · inbound

Truly Self-Improving Agents Require Intrinsic Metacognitive Learning cites this paper.

Truly Self-Improving Agents Require Intrinsic Metacognitive Learning DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 3

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no resolver link, observed 2026-08-07T10:28:16.963397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:28:16.963397Z digest=sha256:fbe465b023afbb6e07698072cc51d1c8e5983ea7de701900d0f4d8316d949ebd

Observation f7779880-9179-40b0-808c-83717c266519 · inbound

SWE-Dev: Building Software Engineering Agents with Training and Inference Scaling cites this paper.

SWE-Dev: Building Software Engineering Agents with Training and Inference Scaling DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2024

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no resolver link, observed 2026-08-07T05:36:02.295962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:02.295962Z digest=sha256:e637a606a50237768580f8ec2234227bcbfa662d28aa8c85a7f1c890b81660bf

Observation c4d4bed2-1749-4bfe-ac01-17c9343ec65b · inbound

Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction cites this paper.

Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 20

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no resolver link, observed 2026-08-07T05:27:49.964683Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:27:49.964683Z digest=sha256:6112996173aa79202aabede63ca43c85a71d6532b4457b5f6e0a0a5dea34bee6

Observation ad01e14f-f568-4893-a43d-b0afa9e9de4c · inbound

GUI-Reflection: Empowering Multimodal GUI Models with Self-Reflection Behavior cites this paper.

GUI-Reflection: Empowering Multimodal GUI Models with Self-Reflection Behavior DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 7

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no resolver link, observed 2026-08-07T05:25:59.230422Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:25:59.230422Z digest=sha256:e6aef0147c9a37116401e209fc7ee7d125a042c9a4a6a716354d0f34c24773ef

Observation e3d773ef-5b92-40cf-8a11-0faa6e9b0f1d · inbound

Atomic-to-Compositional Generalization for Mobile Agents with A New Benchmark and Scheduling System cites this paper.

Atomic-to-Compositional Generalization for Mobile Agents with A New Benchmark and Scheduling System DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 6

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no resolver link, observed 2026-08-07T05:04:02.686260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:04:02.686260Z digest=sha256:d8d8ef3ff50dd702688c9b7dc00b3e6e3766377c5ad75d76be6bc55bebdaf814

Observation b1845b36-9aef-465d-ba2f-98b444bc38cf · inbound

Morae: Proactively Pausing UI Agents for User Choices cites this paper.

Morae: Proactively Pausing UI Agents for User Choices DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 9

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no resolver link, observed 2026-08-05T14:22:41.778339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:22:41.778339Z digest=sha256:e816b529a22a8646df48f46f9683b4f99c9cb8762298929da8e354ccb8bf069e

Observation 47da6e38-1052-4529-9f20-6bc6fe3661f4 · inbound

RoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning cites this paper.

RoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 5

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no resolver link, observed 2026-08-04T09:33:37.516249Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:33:37.516249Z digest=sha256:6b68b475d8553b03e6cbf0a8ce7586e743f06a258790ce01c879c63594cf3622

Observation 355963d0-0bc2-43bb-bc9d-3e7e4c12e1b3 · inbound

GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL cites this paper.

GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 4

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no resolver link, observed 2026-08-02T20:51:40.057308Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T20:51:40.057308Z digest=sha256:85c229caa3ee4d168041fb9b9a327034526c186f00082e27b23586d460407ebf

Observation 53699552-90cd-4730-b690-5bdb26881479 · inbound

Imperfectly Cooperative Human-AI Interactions: Comparing the Impacts of Human and AI Attributes in Simulated and User Studies cites this paper.

Imperfectly Cooperative Human-AI Interactions: Comparing the Impacts of Human and AI Attributes in Simulated and User Studies DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 7

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verified exact
arxiv_id, observed 2026-05-10T09:43:49.218927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-10T09:39:56.132765Z digest=sha256:334a5ba4f91a2aa5b9ba91653eb5ea80fdb8ed02f132a5952c594e0316426eae

Observation eb2eff33-30b9-4595-b298-bec0008e8fee · inbound

X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction cites this paper.

X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 3

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arxiv_id, observed 2026-05-11T18:41:08.618088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T14:53:52.019677Z digest=sha256:da979e64592cda84e4fd8d9576403c470040de590628a9e33e53cb93c59f64f2

Observation 11d4a26d-5163-4211-9e2e-361aea54fa1a · inbound

X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction cites this paper.

X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 4

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arxiv_id, observed 2026-05-22T09:51:21.735886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-22T09:50:00.415616Z digest=sha256:f495d515df061796a0dc06888ba50cbf802f6432698f6092756696d0dc00d255

Observation 2d464d1f-8714-4984-b0d5-5b6250ad749c · inbound

DragOn: A Benchmark and Dataset for Drag-Based GUI Interactions cites this paper.

DragOn: A Benchmark and Dataset for Drag-Based GUI Interactions DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 2

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arxiv_id, observed 2026-06-28T01:41:29.389207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-28T01:37:45.812577Z digest=sha256:81bcd4c34543dc4f8b34e2a3381efebd373a6fc84eebe762ca9d5f5faf36170f

Observation 5095580d-68f3-4e5c-a0ef-84c1e6dfbb58 · inbound

AliyunConsoleAgent: Training Web Agents in Real-World Cloud Environments via Distillation and Reinforcement Learning cites this paper.

AliyunConsoleAgent: Training Web Agents in Real-World Cloud Environments via Distillation and Reinforcement Learning DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 1

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arxiv_id, observed 2026-07-03T01:47:31.155254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-27T16:22:05.424293Z digest=sha256:fa4015d8310df8649228fcc9062244ffc19e4f89916f96963196a75e765a27ee

Observation 8fa9f138-1523-4d8c-a5d8-3db86f1ace14 · 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 DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 4

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arxiv_id, observed 2026-06-30T07:14:21.216457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T07:10:38.909339Z digest=sha256:0d5ff2b545b3dcd6f2caabad228ebaacce014f623fbc2cd744b33d5b3e5a0f7c

Observation 129e80f9-a4f3-44e4-b245-d3d53b26c939 · 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 DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 4

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no resolver link, observed 2026-07-15T10:24:53.345620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T10:24:53.345620Z digest=sha256:83d046af55fc7cfc552f7e4968d2785d4f27af02c37cbaaffdeb483644ed56af

Observation becb788d-5be3-4eb4-b251-72025671a35b · 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 DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Reference 5

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no resolver link, observed 2026-07-31T02:18:01.580579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:18:01.580579Z digest=sha256:5477760d98f9fb39a795610d57666db472c5a8cce96b2953ccb61fa6e733fa6d