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Paper Citation Record · LEDGER

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

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 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 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:37:54.519563Z

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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  • 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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T11:08:27.472508Z digest=sha256:e1ad06fe0f080ea2969cba0ad5553b88df7dd7cb6afc745600371aebbb0f6f5a

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=sha256:91ced51b08d5a0d752c923da300d7dbc8de9b98b5dba0128789d0fc2bd3a851c

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:e34c9db245b6e3d9fb57f071ece4f93298e0383683be0af32f16ef03e0797ee0

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T06:01:31.581813Z digest=sha256:546ecee267bf060a897b0febf63381e0af9d71edbc298f635cbbfc0f4e692f69

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=sha256:00015383109aceee6aaf927c5cc73805cb04ef9010948a3fe2a717e8e5806e79

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T21:32:18.491541Z digest=sha256:3d8d234b337666820a498a99fdbdd335152e062174a618a73edc0621e061f193

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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verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T21:39:49.832151Z digest=sha256:f4cd3cf97f30fac2567f0cf815a0634b6b8879dd4bd54598f9cd49375fb1f1eb

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:c001662892a72027a3047317013ecfd224d2eb9cc851749a58aff14d0006b57e

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:cbfb7c8c3e520327d8d2845833104c99fd52c9bb3e2a69d39b59aca2a95c6452

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=sha256:39bd5dbf52f7497ac6ffd23e17f209aae1014c03e85e73081670ca70f6d8491f

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:27:49.964683Z digest=sha256:e4a62cf6e7ad182f4da11a4bb1dfff890c041036ee604d7617e183cb18ea4242

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:25:59.230422Z digest=sha256:c41c58e65585225cbbefe855fe2445c6099160d5a018c823534071e923d3aacc

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:beee58c89237f8274ac9922a2a1ddee8f7d0c15f6e197d4b748699a152934388

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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unresolved
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=sha256:1faa9d3979f54c35729f3dc67e9e3d5134893724bcea6f6857f70c13fbbcd307

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:33:37.516249Z digest=sha256:0e87c5dd672fe009db081b30a5a792b389d6d66c472c844321d1f32502a37e68

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T20:51:40.057308Z digest=sha256:6ac75c2e39abd53a5af62c40c65d69468344961fedb454ef068adb39b320d282

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T09:39:56.132765Z digest=sha256:71b50290217e1fcd60c2747b899d374a93d7edfe508d51abe40c1e7d34e06633

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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verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T14:53:52.019677Z digest=sha256:0b529742bd42b01b633bed9bbf65d61c2e103ecebbd1aa01baa255f4e69e6508

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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verified exact
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T09:50:00.415616Z digest=sha256:884ae09f69334977bc4a0c45422ff7d0ca782ce0f3988b9b9860fd6fced28568

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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metadata mismatch
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T01:37:45.812577Z digest=sha256:00823ef44d1ee02c528713bfa9a33cbf27c38b05e925c2e62cea37e845bf6711

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T16:22:05.424293Z digest=sha256:53e315d37aae6c03881db969a2eb07dee9c52a0dbb9bb837140ffadddb5a9dc4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T07:10:38.909339Z digest=sha256:61327dc0a536b319ce233f2da9d683c654af2d078772dbc869efc422fd433063

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:c34b1a4428663b7123556baf53118ab085919b251893517e2397e903a133189e

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:18:01.580579Z digest=sha256:f3757f5118f3f7ab35ff26f5383005313e41a772bdac152b0a1b23a908072aba