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Paper Citation Record · LEDGER

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution

As of 6 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2608.03483.

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

pith.paper-citation-record.v1
2608.03483 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:20:27.081386Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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  • verified fuzzy5
  • unresolved29
  • parse uncertain0
  • malformed identifier0
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External citation measurements

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Outbound references

Observation 417206b4-c8f3-4b99-b9a8-006ae16bf22e · outbound

This paper cites SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning

Reference 1

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Observation 7e12955e-2eaf-4e2a-b656-46dcd39416d9 · outbound

This paper cites arXiv preprint arXiv:2510.25889 , year=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution arXiv preprint arXiv:2510.25889 , year=

Reference 2

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source=arxiv_source observed=2026-08-05T18:20:24.124850Z digest=sha256:14d228815bed6827181a2a54f70288aeeda7e77bfc1223b7f19eee853747439c

Observation 05cb194f-780e-4320-8337-dbaf6d2f91c0 · outbound

This paper cites an unresolved cited work.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Unresolved cited work

Reference 3

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source=arxiv_source observed=2026-08-05T18:20:24.246252Z digest=sha256:d5827f8f21b87d3c17fde91f2cf44b0a9b08157fc2da2c5de6c60d9c5de24a2a

Observation 357afb98-abda-4a61-b0ed-64e5bc7993f6 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Advances in Neural Information Processing Systems , volume=

Reference 4

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source=arxiv_source observed=2026-08-05T18:20:24.408172Z digest=sha256:2105bf1d82a3fcd944ccdd7daa942f59faba6cad1d9b48afee8e9a679463170e

Observation f2f9b43b-ec8e-47e6-9f36-d59dfc3b4a96 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Advances in Neural Information Processing Systems , volume=

Reference 5

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raw_fallback, observed 2026-08-05T18:20:27.464816Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-08-05T18:20:24.490194Z digest=sha256:234ae06da2ea9e717cc391409e57e7944807a77081ad54ca4f44f06eb6b9f9a7

Observation eb196054-d326-4834-a681-f4ab781e7d77 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 6

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source=arxiv_source observed=2026-08-05T18:20:24.609676Z digest=sha256:1372742fda17bf199080428fae22cdd694794c4eccca9254837b6164dfaefd67

Observation 5fe160b3-d508-47ba-a5a7-cb20bdd8285e · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 7

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source=arxiv_source observed=2026-08-05T18:20:24.731118Z digest=sha256:40ad1942ad94f88ee417b80847536dc0571204f0a6f55a7e0ca66ec34b4a89e2

Observation 277264eb-6692-45e8-bf34-3735063e1487 · outbound

This paper cites VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies

Reference 8

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source=arxiv_source observed=2026-08-05T18:20:24.819002Z digest=sha256:a233d03ddd01b2b257599601886010ac690d111e154f71be39a5d1071ab6dbde

Observation 878f5d91-f12d-4874-91bf-3ffb513f6adb · outbound

This paper cites an unresolved cited work.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Unresolved cited work

Reference 9

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Observation e93ef478-bd15-4be4-9861-96bf0c21e49e · outbound

This paper cites Mixture of Horizons in Action Chunking.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Mixture of Horizons in Action Chunking

Reference 10

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source=arxiv_source observed=2026-08-05T18:20:25.061646Z digest=sha256:b3ae628c8da84eeea1a36885b159c3f0222e36e62946b59cdaa55c654e549890

Observation 5a5b9b2b-393e-4bc6-989c-3eed2810600f · outbound

This paper cites Open-Loop Planning, Closed-Loop Verification: Speculative Verification for VLA.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Open-Loop Planning, Closed-Loop Verification: Speculative Verification for VLA

Reference 11

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source=arxiv_source observed=2026-08-05T18:20:25.144390Z digest=sha256:e9c335bb94e8d286cc986ba1e847a4387b4debed73e50177aaf77777ef973f37

Observation f015a495-21a9-4b73-aae4-a89881605162 · outbound

This paper cites When to Trust Imagination: Adaptive Action Execution for World Action Models.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution When to Trust Imagination: Adaptive Action Execution for World Action Models

Reference 12

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source=arxiv_source observed=2026-08-05T18:20:25.309628Z digest=sha256:5a0c08f5784853b0eb281162d8bf388223fab1ff29cae459e54dcde57bdea56a

Observation c169fd2f-6c63-49b3-aac4-5c15e0bda5e3 · outbound

This paper cites Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 13

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source=arxiv_source observed=2026-08-05T18:20:25.376639Z digest=sha256:da4be5529dddff17c5d9f526a438dcf26cb185c74154372463a9e0de88b3c4f2

Observation ad02ee7a-ab63-4362-9da6-ce4382542869 · outbound

This paper cites The International Journal of Robotics Research , volume=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution The International Journal of Robotics Research , volume=

Reference 14

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source=arxiv_source observed=2026-08-05T18:20:25.520723Z digest=sha256:bbfb2b289512c6d50288ca085170786c672588cdf47e067dcf7a8fd97a19285c

Observation 1ac2a82c-ccbe-4ea1-9d47-6f9b4e0e32b1 · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution OpenVLA: An Open-Source Vision-Language-Action Model

Reference 15

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source=arxiv_source observed=2026-08-05T18:20:25.591412Z digest=sha256:4a99462de941eff366cabd2cb32161beedd7dbb792a67a042081b97cf861f569

Observation 6549bee3-fad2-4a8d-9f8f-da991ab47e3f · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 16

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source=arxiv_source observed=2026-08-05T18:20:25.696118Z digest=sha256:5f316d58e053aa85099bb39b61d08ac860fbe8c13d8b89e2c2cbf6bb0e3ea97f

Observation 76f93bf9-fd10-4771-9c3e-4c90d4473afe · outbound

This paper cites CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation

Reference 17

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source=arxiv_source observed=2026-08-05T18:20:25.797178Z digest=sha256:df7e9685ac731e08df61f3761bcbe6f8b0c82d21172f536502dd2f8fb325575b

Observation 84422a43-7ad4-454d-b781-35d6fd910ece · outbound

This paper cites Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

Reference 18

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source=arxiv_source observed=2026-08-05T18:20:25.877651Z digest=sha256:4210b4f97aac423632d37d2d1528460b4f7e65aaba1a999e2bc13d4eedefda18

Observation 4d46bc9c-5ced-4901-99c1-2702592436bc · outbound

This paper cites Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Reference 19

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source=arxiv_source observed=2026-08-05T18:20:25.956607Z digest=sha256:b7553ccb615bbd43106e8b2707dec0ef72994474d14e6ff189f63d4294e49dee

Observation 65c98d11-33fb-4040-ae3d-f18de3e0d0ee · outbound

This paper cites A Pragmatic VLA Foundation Model.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution A Pragmatic VLA Foundation Model

Reference 20

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source=arxiv_source observed=2026-08-05T18:20:26.039425Z digest=sha256:33be49a02e90193ebe6ea4fa4f71bca2c49859404dfce6fb57f2ee0ec81e4de3

Observation d55f1ee2-fec0-4fc7-85f2-63e144a1e379 · outbound

This paper cites X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model

Reference 21

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source=arxiv_source observed=2026-08-05T18:20:26.118582Z digest=sha256:e19c828d0e8ca9c50426865e77d65b438bedff8974023f7caec33b918ee29652

Observation feb21191-4ec7-4552-a65f-ff41ca310a1b · outbound

This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 22

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Observation e45e8363-db8d-46e4-a6d8-ec78dace4b2f · outbound

This paper cites RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation

Reference 23

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source=arxiv_source observed=2026-08-05T18:20:26.299200Z digest=sha256:6f2f88bed66a02e1d2807a1eb5c2c548c2d0fb9527f32d1fa542988d9c301c43

Observation 2dd28501-a7d8-4f74-872c-ddd98c7110bb · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Advances in Neural Information Processing Systems , volume=

Reference 24

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source=arxiv_source observed=2026-08-05T18:20:26.376003Z digest=sha256:ab75eff089dd936d93c4aabf12c3b39e9cd6a51e3d9e1658df10972a940f0dfe

Observation db1415c9-8fe4-454a-b9f6-0315955cbe82 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 25

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source=arxiv_source observed=2026-08-05T18:20:26.480336Z digest=sha256:de69ddc15bddf9b3bcd7c6455f69bbb7d1da3772728c83300b2c491af11ca838

Observation a64d72d5-22c6-44e4-a6bb-4ff4dc446d24 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Advances in Neural Information Processing Systems , volume=

Reference 26

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source=arxiv_source observed=2026-08-05T18:20:26.557688Z digest=sha256:60d755695c65df6564be3fd4f47a9a084072355b91fdfda6717e6c8b298d3043

Observation bd301587-4a83-42a5-a3fa-35e8f2089add · outbound

This paper cites LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization

Reference 27

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source=arxiv_source observed=2026-08-05T18:20:26.670826Z digest=sha256:c766f8572114fb94b1c7fb500d6aedc3a52c80043a7944276dd3bd40954cdb1b

Observation 002b8005-4181-4f0a-a823-d32bddbfab69 · outbound

This paper cites ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning

Reference 28

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source=arxiv_source observed=2026-08-05T18:20:26.753857Z digest=sha256:9ea55f73fea7b9404a8d509d04ea5e52c2e83994e3bf34dc796d3402fd57132f

Observation e1952943-b961-4c65-af26-3a435b1ef31f · outbound

This paper cites VLA-Corrector: Lightweight Detect-and-Correct Inference for Adaptive Action Horizon.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution VLA-Corrector: Lightweight Detect-and-Correct Inference for Adaptive Action Horizon

Reference 29

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local_arxiv, observed 2026-08-05T18:20:27.157148Z

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source=arxiv_source observed=2026-08-05T18:20:26.835871Z digest=sha256:d8ecd0aa868d95bfbb01e8371a5efb20f8d227d9cdd7aa0764d40285df502ed3

Observation c552915b-35ec-42f7-ac5b-4ccd4410918f · outbound

This paper cites 20th USENIX Symposium on Operating Systems Design and Implementation (OSDI 26) , pages=.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution 20th USENIX Symposium on Operating Systems Design and Implementation (OSDI 26) , pages=

Reference 30

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source=arxiv_source observed=2026-08-05T18:20:26.839279Z digest=sha256:939b2be998d9e0e87f55e02df934847e861582fc0df22a4cd527049375389abd

Observation 3d1961f1-df65-4954-a987-d8c078dc4d67 · outbound

This paper cites an unresolved cited work.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Unresolved cited work

Reference 31

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source=arxiv_source observed=2026-08-05T18:20:26.869186Z digest=sha256:1e3d5a27d8ca91b005039c7a29548d1b34d1297e10a549b6c849c3db39280339

Observation f2a682ab-d1e2-42e3-b823-50c80b7d5d60 · outbound

This paper cites Causal World Modeling for Robot Control.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Causal World Modeling for Robot Control

Reference 32

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source=arxiv_source observed=2026-08-05T18:20:26.939320Z digest=sha256:d14c5d6a237030b800e3957d5313df98635cb8840066de9fa27ea8f2f9c5c649

Observation 3b6908e9-8d29-418d-b2d1-5a508ee82f1d · outbound

This paper cites Motus: A Unified Latent Action World Model.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Motus: A Unified Latent Action World Model

Reference 33

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source=arxiv_source observed=2026-08-05T18:20:27.021911Z digest=sha256:43297a6d62b2142da8421605133c7a5711490745df7ebc6a07ac86ff243b36ae

Observation b369b99b-397b-4d40-9518-14ad3a33b48e · outbound

This paper cites Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Reference 34

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source=arxiv_source observed=2026-08-05T18:20:27.078140Z digest=sha256:d7461fc55a5bcc7cda791fec08cb1cac044e7dee79b0d6da3c56c4ac925e7769

Observation 6c904911-e3af-4b8e-9a1a-b8b9244f156b · outbound

This paper cites World Action Models are Zero-shot Policies.

Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution World Action Models are Zero-shot Policies

Reference 35

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source=arxiv_source observed=2026-08-05T18:20:27.081386Z digest=sha256:f9cd73a94774955c332d1a72d2b9b4c8986dfee7b4aec13c5a5d6fd18c6aa3dd

Pith citing papers

No inbound Pith citation observations are available.