Paper Citation Record · LEDGER

Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2109.11978.

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

pith.paper-citation-record.v1
2109.11978 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:50:11.167208Z

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

verified exact0
verified fuzzy0
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External citation measurements

101
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 6696e8fd-b032-4923-af16-a615fe5efbc7 · inbound

HuMam: Humanoid Motion Control via End-to-End Deep Reinforcement Learning with Mamba cites this paper.

HuMam: Humanoid Motion Control via End-to-End Deep Reinforcement Learning with Mamba Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T15:51:50.669910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfaa350b-4deb-4aa6-93e7-7264d043b1c4 · inbound

KiVi: Kinesthetic-Visuospatial Integration for Dynamic and Safe Egocentric Legged Locomotion cites this paper.

KiVi: Kinesthetic-Visuospatial Integration for Dynamic and Safe Egocentric Legged Locomotion Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T14:43:59.131592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 334138f3-2d2e-4a0c-8653-288e3f3413ea · inbound

Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning cites this paper.

Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:52:33.775213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e65fbe94-dd4b-4250-8b1b-481caed6fbfa · inbound

Sim2Swim: Zero-Shot Velocity Control for Agile AUV Maneuvering in 3 Minutes cites this paper.

Sim2Swim: Zero-Shot Velocity Control for Agile AUV Maneuvering in 3 Minutes Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 866

Resolution: unresolved; no resolver link, observed 2026-08-03T17:39:11.090248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e453db3b-2d6b-42a9-b3da-c67dffaea1ed · inbound

LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller cites this paper.

LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:28:23.847565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6506e0a6-8304-4130-9834-3536ac5d70bd · inbound

Neural Assistive Impulses: Synthesizing Exaggerated Motions for Physics-based Characters cites this paper.

Neural Assistive Impulses: Synthesizing Exaggerated Motions for Physics-based Characters Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:00:48.467691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 60098fd0-2727-4dc9-ac1f-1a31e393c0fd · inbound

SigLoMa: Learning Open-World Quadrupedal Loco-Manipulation from Ego-Centric Vision cites this paper.

SigLoMa: Learning Open-World Quadrupedal Loco-Manipulation from Ego-Centric Vision Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-12T00:11:17.706807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 08ab8680-a352-489b-bbf3-277799f12320 · inbound

Efficient On-policy Visual-RL via Stochastic Decoupled Policy Gradient cites this paper.

Efficient On-policy Visual-RL via Stochastic Decoupled Policy Gradient Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:03:48.582335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aa81de37-b181-412d-a592-715729be0dd6 · inbound

Real-IKEA: Physical Fidelity is the Prerequisite for Robust Manipulation cites this paper.

Real-IKEA: Physical Fidelity is the Prerequisite for Robust Manipulation Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:17:29.864617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 66805cec-6e97-429c-827b-303c00a57e35 · inbound

Tracking the Effective Surface Area of Non-Convex Satellites cites this paper.

Tracking the Effective Surface Area of Non-Convex Satellites Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-27T15:31:00.472681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bb7d2dce-2d78-4686-a2f2-1a8b07cfd53c · inbound

Do as I Do: Dexterous Manipulation Data from Everyday Human Videos cites this paper.

Do as I Do: Dexterous Manipulation Data from Everyday Human Videos Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:59:19.491757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 072e22d4-eb5e-4d14-a741-d2a53da2e421 · inbound

Unleashing Infinite Motion: Scaling Expressive Quadrupedal Motion via Generative Video Priors cites this paper.

Unleashing Infinite Motion: Scaling Expressive Quadrupedal Motion via Generative Video Priors Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-01T17:05:51.257955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4145546a-2be1-4287-939a-8cd0b7579b6c · inbound

Milo, a Fully Autonomous Indoor/Outdoor Robotic Guide Dog cites this paper.

Milo, a Fully Autonomous Indoor/Outdoor Robotic Guide Dog Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T12:31:21.159967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a76c281-1f55-4f8f-ac52-8240c310737b · inbound

Towards Miniature Humanoid Tele-Loco-Manipulation Using Virtual Reality and Reinforcement Learning cites this paper.

Towards Miniature Humanoid Tele-Loco-Manipulation Using Virtual Reality and Reinforcement Learning Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T09:58:57.023092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68e1e66d-4eae-4f6a-b47e-19f2bd22b0c6 · inbound

When Is a Learned Command Adapter Worth It? Closed-Loop Identification and Counterfactual Auditing of Frozen Locomotion Policies cites this paper.

When Is a Learned Command Adapter Worth It? Closed-Loop Identification and Counterfactual Auditing of Frozen Locomotion Policies Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T06:32:51.170921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebb70748-2f9e-4da4-8aeb-b4543c30fa2a · inbound

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills cites this paper.

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 217

Resolution: unresolved; no resolver link, observed 2026-08-04T19:45:35.176096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f022b49-bb8b-4a64-ba4b-48bdb5456236 · inbound

GASP: GPU-Accelerated Safe Planner for Real-Time Collision-Aware Motion Generation with Latent Trajectory Sampling cites this paper.

GASP: GPU-Accelerated Safe Planner for Real-Time Collision-Aware Motion Generation with Latent Trajectory Sampling Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T20:50:11.167208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.