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Paper Citation Record · LEDGER

Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2410.21845.

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

pith.paper-citation-record.v1
2410.21845 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:46:40.656431Z

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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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 f1e3aadc-b9aa-4feb-82ed-dabeb2145b61 · inbound

RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning cites this paper.

RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 26

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no resolver link, observed 2026-08-11T16:45:08.286467Z

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source=arxiv_source observed=2026-08-11T16:45:08.286467Z digest=sha256:f920fa650e2b3928c0de54156bef509e6b86c10199560cf7a1b0fd10a5f6f0f8

Observation 5b45896e-b92b-4b8d-a514-ee771490c344 · inbound

ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy cites this paper.

ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 20

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source=pdf_text observed=2026-08-08T19:20:33.623613Z digest=sha256:dbced0e67573fd671bb7264cf9d1eb8cb74dfa0459f7ba7dec11e875037443a2

Observation 38565bfe-6d09-46f8-825e-46776006dc07 · inbound

AhaRobot: A Low-Cost Open-Source Bimanual Mobile Manipulator for Embodied AI cites this paper.

AhaRobot: A Low-Cost Open-Source Bimanual Mobile Manipulator for Embodied AI Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 14

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arxiv_id, observed 2026-05-23T00:02:17.527612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-23T00:00:53.307042Z digest=sha256:4fc54db67a4f79c388da5f77af40b7d6b1b8d8cf5adf55fef483d4c7ff9cedfe

Observation d7aad825-a44d-4d10-9945-ac9067e8aa22 · inbound

SIME: Enhancing Policy Self-Improvement with Modal-level Exploration cites this paper.

SIME: Enhancing Policy Self-Improvement with Modal-level Exploration Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 22

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source=pdf_text observed=2026-08-16T04:24:21.418807Z digest=sha256:91c8d39da99d38943a9cbeeaf6a8b22af64414a13e22f27fd6d42eea8779486c

Observation 7bbaf9ad-e687-46f8-81af-89a711b41d08 · inbound

A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI cites this paper.

A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 109

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source=pdf_text observed=2026-08-16T04:46:40.656431Z digest=sha256:77799ec2e88fd78b0f1ec3b831805f71c71895ee6849fc35019bc8e38f85016d

Observation 19339de0-8164-426f-9493-e3246be2c0e8 · inbound

Robust Model-Based In-Hand Manipulation with Integrated Real-Time Motion-Contact Planning and Tracking cites this paper.

Robust Model-Based In-Hand Manipulation with Integrated Real-Time Motion-Contact Planning and Tracking Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 39

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no resolver link, observed 2026-08-15T23:21:33.451032Z

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source=arxiv_source observed=2026-08-15T23:21:33.451032Z digest=sha256:944c38b1549aa9c0d86638695152376b82caded0322f4149ec09f10ccc84eb14

Observation 9d91a8f3-2dce-4bc8-ad99-7f8c97766881 · inbound

Zero-Shot Sim-to-Real Reinforcement Learning for Fruit Harvesting cites this paper.

Zero-Shot Sim-to-Real Reinforcement Learning for Fruit Harvesting Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 3

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no resolver link, observed 2026-08-15T21:57:44.372602Z

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source=pdf_text observed=2026-08-15T21:57:44.372602Z digest=sha256:1fefa7cd1478d94d39b40e405d14186fbf5cb9f677abc049946c4a8a14936e9d

Observation ee8914a1-eee1-4f35-8869-de0cc19e0a51 · inbound

Bootstrapping Imitation Learning for Long-horizon Manipulation via Hierarchical Data Collection Space cites this paper.

Bootstrapping Imitation Learning for Long-horizon Manipulation via Hierarchical Data Collection Space Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 17

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no resolver link, observed 2026-08-07T14:51:42.390470Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:51:42.390470Z digest=sha256:8bf69d9e9109928bb2446d5bc6992f6f5eb3f87aff1dd53ce7b7df8cfa9cb5fa

Observation 77728afb-05ac-4ec6-ac06-10df5faab142 · inbound

VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning cites this paper.

VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 51

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arxiv_id, observed 2026-05-16T12:55:40.477240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T12:55:40.245908Z digest=sha256:bbf7e61b52244cf4abd0bb5876ce37f1eb1473a771a0302037051c4223c327db

Observation 317c1489-65bc-4a26-9f5b-844fd14b6e39 · inbound

TeViR: Text-to-Video Reward with Diffusion Models for Efficient Reinforcement Learning cites this paper.

TeViR: Text-to-Video Reward with Diffusion Models for Efficient Reinforcement Learning Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 55

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source=pdf_text observed=2026-08-07T14:12:39.869877Z digest=sha256:0775c9fa7b8d18135a571c68ab1d38bd587afdcdd08e7b2c2574c9769ae682ca

Observation 216a3b5f-2cca-4dda-a44d-aae64872c4a7 · inbound

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials cites this paper.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 37

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source=pdf_text observed=2026-08-07T13:26:30.534038Z digest=sha256:0f7608514abbe4f682e20790b7b4f4c901db58933a4c16897685fc1af7f8da1f

Observation f8b129b2-404d-4769-bf16-c2b5fe35ae10 · inbound

Steering Your Diffusion Policy with Latent Space Reinforcement Learning cites this paper.

Steering Your Diffusion Policy with Latent Space Reinforcement Learning Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 92

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arxiv_id, observed 2026-05-17T21:55:46.378636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-17T21:55:46.183007Z digest=sha256:1f9a777d0eb6814e39233d11acdfca610a194f7360ae3e0e92d4a27c0c7006e0

Observation c31bab30-118e-4053-bfa5-6ce9bce6b9a2 · inbound

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training cites this paper.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 9

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source=pdf_text observed=2026-08-06T19:53:06.156942Z digest=sha256:5bcdb21b3fc12d585da9bdaed5e2e51a6aec9cefdfd029542b254f7e2a93e764

Observation 9dc67e93-ef6d-407f-9103-e88f2284cb14 · inbound

Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey cites this paper.

Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 186

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arxiv_id, observed 2026-05-17T20:28:16.153201Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-17T20:28:15.818016Z digest=sha256:315f0947885aedc0d236a3d66d35e35329ed24bb05fc8aeff2fac4fdf3b4299c

Observation de1e985f-4095-4003-86bd-f0f7ef090805 · inbound

RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction cites this paper.

RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 32

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no resolver link, observed 2026-08-04T21:32:58.738256Z

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source=pdf_text observed=2026-08-04T21:32:58.738256Z digest=sha256:d0f8529f87882d215161100d6af48c8ab2803720fa446f44496502907b1a92f2

Observation eba7aca7-3f7f-48da-b255-f1969568a990 · inbound

BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives cites this paper.

BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 7

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source=pdf_text observed=2026-08-15T15:52:38.386747Z digest=sha256:0bdc001170edfe98e474dd85fcfe8276e54212f8280b42fae1914819d6e5f35f

Observation 35d57a6d-18d2-4683-8c9e-94b5a60bc653 · inbound

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation cites this paper.

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 3

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arxiv_id, observed 2026-05-08T21:49:16.190040Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T11:22:38.704101Z digest=sha256:4e1cc3bd10fee6eaf4c30c8a101dd4d1e31edce5f129398634432dee7a86d20b

Observation 6128db45-81fe-4d46-a060-44e6b2491e29 · inbound

RL Token: Bootstrapping Online RL with Vision-Language-Action Models cites this paper.

RL Token: Bootstrapping Online RL with Vision-Language-Action Models Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 5

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arxiv_id, observed 2026-05-11T19:26:09.145629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T11:56:34.978806Z digest=sha256:c4b0bfa7838dbc11f0b564cf04f97b41850f4a4bd521ad8b262de1fca86326e6

Observation 3c15f417-0eb5-4a56-a0fe-eea2731febd1 · inbound

$M^2$-VLA: Boosting Vision-Language Models for Generalizable Manipulation via Layer Mixture and Meta-Skills cites this paper.

$M^2$-VLA: Boosting Vision-Language Models for Generalizable Manipulation via Layer Mixture and Meta-Skills Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 16

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arxiv_id, observed 2026-05-11T22:11:16.082966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T03:13:36.437080Z digest=sha256:83f723285236a9b3c75fb22764d83ec078a4104f6afdeb647fd150af2264e510

Observation dc00898e-6956-4cab-a03d-3658d7f48fcc · inbound

$M^2$-VLA: Boosting Vision-Language Models for Generalizable Manipulation via Layer Mixture and Meta-Skills cites this paper.

$M^2$-VLA: Boosting Vision-Language Models for Generalizable Manipulation via Layer Mixture and Meta-Skills Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 14

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no resolver link, observed 2026-07-12T18:17:43.564400Z

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source=pdf_text observed=2026-07-12T18:17:43.564400Z digest=sha256:c5ef6cad316c578a8de9097072ba71e198933b906ce93cf697948de800db0ffd

Observation 840af7e9-0fdf-44d9-8603-80182dc035d6 · inbound

REAP: Reinforcement-Learning End-to-End Autonomous Parking with Gaussian Splatting Simulator for Real2Sim2Real Transfer cites this paper.

REAP: Reinforcement-Learning End-to-End Autonomous Parking with Gaussian Splatting Simulator for Real2Sim2Real Transfer Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 21

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arxiv_id, observed 2026-05-12T07:56:27.839204Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-12T01:30:06.120140Z digest=sha256:de3c1590866c305c60f592e9429eeb9530df48e4537dfe5d01d6b0c70917745b

Observation 93ec771b-b6d0-4706-8409-71c1f09eaaf1 · inbound

EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models cites this paper.

EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 3

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arxiv_id, observed 2026-06-29T22:13:59.910904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-29T22:10:08.682307Z digest=sha256:de6feb4251465e3df9c44785bd26a46e5a886954b20049a3dff3f3c731cf6434

Observation af7b178d-c22a-4639-b9d7-ae8bd028a1c8 · inbound

RhinoVLA Technical Report cites this paper.

RhinoVLA Technical Report Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 21

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arxiv_id, observed 2026-07-02T19:17:17.944048Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T21:36:15.806974Z digest=sha256:cea5c3bed68452ed7a1a9c5a1fcfe1380dd4b382905dc1f68063ea6cf9c69555

Observation e72926d9-f91b-489a-b804-f1fa40e5d63c · inbound

RhinoVLA Technical Report cites this paper.

RhinoVLA Technical Report Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 21

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arxiv_id, observed 2026-07-01T07:15:29.824272Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-01T07:14:14.918962Z digest=sha256:c275688e9405e1acaa53431d1225150bf6a2633f0b3ffecc137124a909307973

Observation 46b0fad7-20ca-42a4-85a7-c2a03c95204a · inbound

RhinoVLA Technical Report cites this paper.

RhinoVLA Technical Report Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 21

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no resolver link, observed 2026-07-12T14:51:51.552221Z

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source=pdf_text observed=2026-07-12T14:51:51.552221Z digest=sha256:1c623d5a3cf6781fa06a44ed63e3cf31eeb8c8e476fb325bc6e5f0185db75df2

Observation c6a2d310-74ff-4307-8a45-c20c6507ef3b · inbound

RhinoVLA Technical Report cites this paper.

RhinoVLA Technical Report Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 21

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no resolver link, observed 2026-08-02T12:15:09.439410Z

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source=pdf_text observed=2026-08-02T12:15:09.439410Z digest=sha256:5a01efdbabe4a96dc5b57be01637545544c9cd4a3a52959f590f0ab707962acf

Observation e593cfcc-629c-4f1a-836d-692b999583ce · inbound

Scaling by Diversified Experience for Vision-Language-Action Models cites this paper.

Scaling by Diversified Experience for Vision-Language-Action Models Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 17

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verified exact
arxiv_id, observed 2026-07-03T00:27:29.749739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T17:12:50.216492Z digest=sha256:5d9dd3e866caa58a325e673138fa34f979a1e0e6c7ecabe89da65326ebed2291

Observation 04b957af-0272-4fe3-ab2a-4d86c2ab0332 · inbound

Improving Robotic Generalist Policies via Flow Reversal Steering cites this paper.

Improving Robotic Generalist Policies via Flow Reversal Steering Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 87

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arxiv_id, observed 2026-07-03T15:48:35.797738Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T06:20:19.209180Z digest=sha256:6ed7ab378ef78be3555dc7a5622528676b518675aab674124c6b265ffa74f34f

Observation a3c39299-0e20-4f32-a11c-bafcdd033e7b · inbound

Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline) cites this paper.

Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline) Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 11

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source=pdf_text observed=2026-08-02T10:06:14.517417Z digest=sha256:83db2d09e56a428b27a841b1550e2d2cfd4eada503314d5dcd933bf991b2e812

Observation d95dd179-3f67-4a83-a865-8737302ef49b · inbound

OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies cites this paper.

OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 22

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source=pdf_text observed=2026-07-12T00:23:04.763773Z digest=sha256:f4ba24a7b039d5ef7f580853597806c282337eeea070a8d66262c93428c74a0f

Observation 80caa631-9739-431b-9cc8-25ac8d85ffb3 · inbound

FlowDAgger: Human-in-the-Loop Adaptation of Generative Robot Policies in Latent Space cites this paper.

FlowDAgger: Human-in-the-Loop Adaptation of Generative Robot Policies in Latent Space Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 20

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no resolver link, observed 2026-07-13T06:05:18.192691Z

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source=pdf_text observed=2026-07-13T06:05:18.192691Z digest=sha256:9712803dd4dd817b17959ad8026b462d9ddc6281b0e857ad13cda04d8801441f

Observation 03af78ad-c107-40e5-820c-216a2d35dd22 · inbound

The Curse of Precision: A Data Scaling Law for High-Precision Robotic Manipulation cites this paper.

The Curse of Precision: A Data Scaling Law for High-Precision Robotic Manipulation Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 34

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source=pdf_text observed=2026-08-01T03:37:50.009306Z digest=sha256:ca6176fbd2bd06c46a10527e89cb598a197b06daf57f2dd340d2dc8f7e61fd03