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Paper Citation Record · LEDGER

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

As of 7 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

  • verified exact0
  • verified fuzzy5
  • unresolved29
  • parse uncertain0
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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=sha256:552499c5e8b737f9c8ff3d36d7fd43138ce5ad637da4d1b18d89c409d7f1a91e

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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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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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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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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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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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:d5e20be2febfdec5314e410c35a6b5e3fe4a758abfb35074d2f5fc827c6c957c

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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source=arxiv_source observed=2026-08-05T18:20:24.947586Z digest=sha256:ef01a27512e5ef0e580b15d32f67c993ce0e1e5c3e4c33c65f5c43132bee9e2e

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=sha256:7a04bf07c8841ce1b115bd23202fed18e6df964a98fdb144576f3cee75767152

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=sha256:52f69d0dc3cb273f765b59ad1f2795448474de2df7a1d8c7bbddb72d084dcb82

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=sha256:0a3b0b98b1eca9ea891f9f3d5c0f9d58df9162ec1927d103c8f6666bb1d7608a

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=sha256:1961f3cde2aaf64a4616a1bbb84463f2559b3418ea3bc3e5f814e880f1ce4e4b

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=sha256:000601d1a8aeb282a6e2dde0ba41abda47d064121d19d2c197d6c7294d8306de

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=sha256:14a500c5a0d3bddd2234f40305129bd6a18f11f4aa86279067a66517e9a9ef63

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:fecd35d7b9fe9f611137f9516f505a4d7d5b37c9d2a6c50e426c7477e3bfe466

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:b2b4fce0a9bc333be768258b4ad0e012c18990eb0010e437460f6dc8462a0afb

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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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=sha256:78c8737a662c5985a85d0303589414481c303d9db0e77ce69869cb22736ffdc4

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:e68df646b56cc30816832c392904830554b48f6a1c841c50e986bd9e4b1bed57

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=sha256:6370e3336f5fd607c29b8126d11cddaaf24d7972149565d44540d29041f24d7e

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:c62eb91c5080f3eedc89937fe37104f237969fa33e308b390c381bf34a83907a

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=sha256:8b6cf73c44c432502673f65d986f2482ff9321ba05ca652101c4d5eef06b8291

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=sha256:69d15ccd35730e57145871ddcb5863c3abffd1495e2c3d859d0044040bb696ef

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:eeaa714cf6d843692a35b57e7194b2118980ddf26155d01342a70e1c29f831a4

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=sha256:8a1a21d330f6389855d65802394fd64fd6055809741176fc00f3fd9001c8a504

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:eb2d80e682228f235e99883a975d6a45aafb9db091c6351cabe391b0e27fde33

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=sha256:01db5b9bd8a3f22837b5da49c6d87b4c422ee7aa1b5a60a69e4426e5389590bd

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=sha256:4e7729e4b5ac6b85d2d79d6b8c361f3de7a0ebbe561526acdb15f295a8d85939

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:e0c9f87f6e8a1e622bcf250feafe6621d9df52ac27d406b9a364db9d8409e915

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:c8c8b491391e86c37301dc8fd0439c654a42cbe10d2673faea84d6e469318a5b

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:bbb72e11f565c91f50c6bd37761a377dc79c08cf072dc94dc6b8adc1445de5a1

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:e6d5794889561b6666133ce8622df4516f27b188febb43c3a71c193b91af8de5

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=sha256:8c701d55632b20d85f0a9e7d29ccbd91d9f69cfe7fc3f44bcc7cdfd4013659a2

Pith citing papers

No inbound Pith citation observations are available.