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Paper Citation Record · LEDGER

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance

As of 14 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2608.09853.

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

pith.paper-citation-record.v1
2608.09853 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:32:48.595901Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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 fuzzy18
  • unresolved16
  • parse uncertain0
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External citation measurements

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Outbound references

Observation c349d18c-dfb7-465e-8a73-9343cca2bf25 · outbound

This paper cites Qwen3-VL Technical Report.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Qwen3-VL Technical Report

Reference 1

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Observation a165dae4-3b6d-41df-9a56-847f0b49e8cd · outbound

This paper cites InProceedings of the Conference on Robot Learning, 2025.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance InProceedings of the Conference on Robot Learning, 2025

Reference 2

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c0dda3ab-8d52-4e4a-a976-39ccacb6bd50 · outbound

This paper cites AgiBot World Colosseum: A large-scale manipulation platform for scalable and intelligent embodied systems.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance AgiBot World Colosseum: A large-scale manipulation platform for scalable and intelligent embodied systems

Reference 3

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Observation b799a5ea-064d-45b4-92c3-4123b836f69b · outbound

This paper cites LeRobot: State-of-the-art machine learning for real-world robotics in PyTorch.https://github.com/huggingface/lerobot, 2024.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance LeRobot: State-of-the-art machine learning for real-world robotics in PyTorch.https://github.com/huggingface/lerobot, 2024

Reference 4

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.478790Z digest=sha256:67f7466be3f5a5aaeb58fa7d81871aeb8125f612093be60348752d2e3b58475c

Observation 7e8ab287-61fa-4750-864f-0216bfb4a877 · outbound

This paper cites RynnBrain: Open embodied foundation models.arXiv preprint arXiv:2602.14979, 2026.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance RynnBrain: Open embodied foundation models.arXiv preprint arXiv:2602.14979, 2026

Reference 5

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source=pdf_text observed=2026-08-11T05:32:48.482927Z digest=sha256:dee1bf9892f435e46dd702e441bde9afd21f0b32f072fe2aee1eba5db31fae17

Observation 19fbaae0-0730-4934-bedd-9cfe902fd8d1 · outbound

This paper cites Unified language model pre-training for natural language understanding and generation.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Unified language model pre-training for natural language understanding and generation

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.487015Z digest=sha256:92b18593a1c24decf3f41f031a539d5f9338bbb567a4c672e3c196cb7fd7e8f7

Observation f8a4e68f-23c5-4767-aaa2-07c55c9d5afc · outbound

This paper cites Stop regressing: Training value functions via classification for scalable deep RL.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Stop regressing: Training value functions via classification for scalable deep RL

Reference 7

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.491350Z digest=sha256:bf6e7fa4378e986d5e7d4eafcae55d5644b84061c79171ac4042ae11fff5805c

Observation 2a46edb3-503a-43c4-9187-a08d6b501b85 · outbound

This paper cites Shortcut learning in deep neural networks.Nature Machine Intelligence, 2(11):665–673, 2020.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Shortcut learning in deep neural networks.Nature Machine Intelligence, 2(11):665–673, 2020

Reference 8

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source=pdf_text observed=2026-08-11T05:32:48.494806Z digest=sha256:831c1890cc1f1eba8a2989a4623f7a2e3cecab96d44470ff600e53f2d8083994

Observation de6652ff-49bc-42fe-b6e4-88f5c5f3417f · outbound

This paper cites Mastering diverse control tasks through world models.Nature, pages 1–7, 2025.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Mastering diverse control tasks through world models.Nature, pages 1–7, 2025

Reference 9

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source=pdf_text observed=2026-08-11T05:32:48.498440Z digest=sha256:7dd885d704272cb445a426346daeb736aa0cc81ab21b1260084af3ac893d4568

Observation aa50b288-3abc-48ea-b6b0-5f897cfba0a5 · outbound

This paper cites EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video

Reference 10

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source=pdf_text observed=2026-08-11T05:32:48.502155Z digest=sha256:462a5e231991149ce41c5845600b8b1ea885229100672e844e2661fe147a0370

Observation ad72e0b7-576f-4245-9a15-84d6cd9c8db4 · outbound

This paper cites FiRE: En- hancing MLLMs with fine-grained context learning for complex image retrieval.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance FiRE: En- hancing MLLMs with fine-grained context learning for complex image retrieval

Reference 11

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source=pdf_text observed=2026-08-11T05:32:48.506028Z digest=sha256:1542447314bdd3c3f7cf91d38b974f8ad8ecd9f6852e93f657a15df9da226210

Observation 745b0c2d-1faa-40da-87ac-81c117d40981 · outbound

This paper cites $\pi^{*}_{0.6}$: a VLA That Learns From Experience.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance $\pi^{*}_{0.6}$: a VLA That Learns From Experience

Reference 12

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source=pdf_text observed=2026-08-11T05:32:48.509349Z digest=sha256:bd7b25a01d8bd8984b2761a34d455732624bd109944fcebdcb50fcba47f4ee3f

Observation bd3379af-6845-456e-b65e-1bc494e9ebef · outbound

This paper cites Galaxea Open-World Dataset and G0 Dual-System VLA Model.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Galaxea Open-World Dataset and G0 Dual-System VLA Model

Reference 13

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source=pdf_text observed=2026-08-11T05:32:48.513096Z digest=sha256:eb67b3f8ddc57b18bb47778d0377ce2da7b0404bb456533b9d9acfabf4ded6fe

Observation 7dc2d07c-fa61-422c-af2d-18e7ea62a824 · outbound

This paper cites Offline reinforcement learning with implicit Q-learning.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Offline reinforcement learning with implicit Q-learning

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.516957Z digest=sha256:2ac343a550a1dd070ec7a93aa12bee6fe99035b57a88badaeb37028f24338500

Observation 1dbf5659-3f55-40b9-acd4-6ab1829be227 · outbound

This paper cites RoboReward: General-purpose vision-language reward models for robotics.arXiv preprint arXiv:2601.00675, 2026.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance RoboReward: General-purpose vision-language reward models for robotics.arXiv preprint arXiv:2601.00675, 2026

Reference 15

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source=pdf_text observed=2026-08-11T05:32:48.520313Z digest=sha256:621d68a260cc127cfc734efa7a4d4c039e35443f8f1e4da36e13df657a96a4a0

Observation 5d2bf1e1-856a-4b59-a0af-a7cebd03f51c · outbound

This paper cites Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons

Reference 16

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source=pdf_text observed=2026-08-11T05:32:48.523516Z digest=sha256:3143ccfb13e9001250139e87a35f3f14c868610e7a762e4b917bd094704e2a78

Observation ed2d972c-5ef6-4251-9a2b-198ee893ba93 · outbound

This paper cites RDT-1B: a diffusion foundation model for bimanual manipulation.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance RDT-1B: a diffusion foundation model for bimanual manipulation

Reference 17

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.527505Z digest=sha256:5d898154cc8d4a8923db67edad34489d1d18fdb713e6725fb65d32f6b3dd8b10

Observation 0e5e173b-0dee-4c70-ab77-98cba3480e39 · outbound

This paper cites TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance

Reference 18

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source=pdf_text observed=2026-08-11T05:32:48.531404Z digest=sha256:f4794f22dc0f6221640921c8402bb067ed7eeadde73d047c7a4906096fbe29e7

Observation b42df604-629c-450a-9164-e1904295e3f3 · outbound

This paper cites Vision language models are in-context value learners.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Vision language models are in-context value learners

Reference 19

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.535408Z digest=sha256:954f37991ebd5243c87b4f57ecd96f34b1c4bf7a9bd14c96c6c20ffcb5992f8a

Observation 22c029c0-64f5-40b1-b666-522eca1ada82 · outbound

This paper cites RoboTwin: Dual-arm robot benchmark with generative digital twins.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance RoboTwin: Dual-arm robot benchmark with generative digital twins

Reference 20

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.539127Z digest=sha256:c4676c9c80f9c611d38d3ed31e1928e67e7125e9e617ca43c81463a0254766e1

Observation 429b123f-dce8-4f35-b199-24c4e74a02f2 · outbound

This paper cites Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control

Reference 21

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.543114Z digest=sha256:196e9f7fdd8187adc88fb0203cbae385fb5959c02103dc7341931ea528909b4c

Observation c03cdd45-37ca-480c-8f42-353d81d8aec2 · outbound

This paper cites Policy invariance under reward transformations: Theory and application to reward shaping.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Policy invariance under reward transformations: Theory and application to reward shaping

Reference 22

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.546786Z digest=sha256:895c7b0b638ac8c73daf952d8b4981e2e1ebba7a482d5adc52633d4060c8426e

Observation 79937961-2ee2-47c2-ad8b-c6a635302651 · outbound

This paper cites Open X-Embodiment: Robotic learning datasets and RT-X models.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Open X-Embodiment: Robotic learning datasets and RT-X models

Reference 23

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source=pdf_text observed=2026-08-11T05:32:48.550369Z digest=sha256:5d7375c822eddba33aa04176acb34198ab7fb869a3cdb69b84eef27ff6e0f48b

Observation 1eaa496b-71d8-4200-8775-21f1bb96b99e · outbound

This paper cites John Wiley & Sons, 2014.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance John Wiley & Sons, 2014

Reference 24

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source=pdf_text observed=2026-08-11T05:32:48.554182Z digest=sha256:e824da225be8e892cdcbd2d2f0dae3fe4b17a66da7fca358b5b2032c2b83c7a9

Observation 00dd8569-ffb3-42e3-a161-732f1e7c0f34 · outbound

This paper cites Universal value function approximators.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Universal value function approximators

Reference 25

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.557670Z digest=sha256:f04f927b45a47e23d530707c1e9dda5c42ef8159f84f844a9629b914c61d5dae

Observation 28b13ea7-eef2-4ee2-857f-41579df08142 · outbound

This paper cites Robo-Dopamine: General process reward modeling for high-precision robotic manipulation.arXiv preprint arXiv:2512.23703, 2025.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Robo-Dopamine: General process reward modeling for high-precision robotic manipulation.arXiv preprint arXiv:2512.23703, 2025

Reference 26

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source=pdf_text observed=2026-08-11T05:32:48.561306Z digest=sha256:a6d3074ac88145bc333e631a8f4bf2ef57ffa7f0115d2384a7077e31652a5115

Observation 351c74ec-0a12-41bf-af5b-3d3551480249 · outbound

This paper cites InternData-A1: Pioneering high-fidelity synthetic data for pre-training generalist policy.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance InternData-A1: Pioneering high-fidelity synthetic data for pre-training generalist policy

Reference 27

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raw_fallback, observed 2026-08-11T05:32:48.983520Z

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source=pdf_text observed=2026-08-11T05:32:48.564797Z digest=sha256:7652d41cbf56acf8d1115c723643be34ce95abb94dfdf4774b14a4471c771427

Observation a5fcf16e-2549-4d75-aa90-c4fffd07e0dd · outbound

This paper cites Steering your diffusion policy with latent space reinforcement learning.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Steering your diffusion policy with latent space reinforcement learning

Reference 28

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.568288Z digest=sha256:f07308b7ae98477ad7fbafafb952c313c702751699e8ba55756bed1c5a523c75

Observation 2e79d696-80aa-40b4-895c-54c0156463e8 · outbound

This paper cites RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation

Reference 29

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source=pdf_text observed=2026-08-11T05:32:48.572467Z digest=sha256:39393f7337ce294ad506c29a207bd7342e16f43fc5efd41ca404b9ecbcab4644

Observation 0c7a8e4e-0052-43df-9882-be2c793ad717 · outbound

This paper cites RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation

Reference 30

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source=pdf_text observed=2026-08-11T05:32:48.576131Z digest=sha256:5ad0d3d4df8d909c8297778548df3a7c9fdcfcad692f0106ae895104125b1dd3

Observation 3522ce36-9afb-4e4e-93c4-af104b06265a · outbound

This paper cites RARM: Confidence-Gated Progress Reward Modeling for RL in Manipulation.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance RARM: Confidence-Gated Progress Reward Modeling for RL in Manipulation

Reference 31

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local_arxiv, observed 2026-08-11T05:32:48.647549Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.580065Z digest=sha256:782e154ad774ce1d68360bc95600abca4d8c36c25226039484373b60cd3cbcfc

Observation 2bce8115-83ad-4522-93cf-d1bc173ff88f · outbound

This paper cites an unresolved cited work.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance Unresolved cited work

Reference 32

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source=pdf_text observed=2026-08-11T05:32:48.583960Z digest=sha256:5d31e4c523945c258c7e4c183e2a7c7503c264dd04f93b5a180ba87a98b8459f

Observation 8afe2dda-66af-4c8e-8901-f071bac1b9b5 · outbound

This paper cites ReWiND: Language-guided rewards teach robot policies without new demonstrations.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance ReWiND: Language-guided rewards teach robot policies without new demonstrations

Reference 33

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raw_fallback, observed 2026-08-11T05:32:48.947428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.587977Z digest=sha256:fad3ac1d800c47757d4ac88f229088269b337a797f75fe513b29832f344723df

Observation a9204c97-86ea-404b-927b-afec7cd48479 · outbound

This paper cites A generalist pair-wise progress critic model for vision-language-action robots.

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance A generalist pair-wise progress critic model for vision-language-action robots

Reference 34

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raw_fallback, observed 2026-08-11T05:32:48.934880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T05:32:48.591813Z digest=sha256:b9a0577f1f812378061386f5cc6b0cfbd381ceefc84fb2dc8f899ed778d48143

Observation a66f0281-1e28-43ff-b182-15ed73fbc7d5 · outbound

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

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model

Reference 35

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