Paper Citation Record · LEDGER

Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2009.13303.

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

pith.paper-citation-record.v1
2009.13303 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:07:26.726567Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:39:16.665490Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation abb060e0-6109-43e4-ba82-5fb638c7e877 · inbound

Stability Enhancement in Reinforcement Learning via Adaptive Control Lyapunov Function cites this paper.

Stability Enhancement in Reinforcement Learning via Adaptive Control Lyapunov Function Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T19:07:26.726567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c011582-2d4a-4b50-b07a-b4809f124fc8 · inbound

Mind the Sim2Real Gap in User Simulation for Agentic Tasks cites this paper.

Mind the Sim2Real Gap in User Simulation for Agentic Tasks Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T05:51:29.482999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a97dae7f-3ab2-4044-8735-02c16bbf5f00 · inbound

EmbodiedGovBench: A Benchmark for Governance, Recovery, and Upgrade Safety in Embodied Agent Systems cites this paper.

EmbodiedGovBench: A Benchmark for Governance, Recovery, and Upgrade Safety in Embodied Agent Systems Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:41:06.756347Z

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.

Observation 5024bfc2-6323-438d-be1f-c9f132b88d28 · inbound

A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning cites this paper.

A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-12T13:42:27.758405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48ad46e5-3a88-49cf-8e4f-303e2db50cc7 · inbound

Object-Centric Residual RL for Zero-Shot Sim-to-Real VLA Enhancement cites this paper.

Object-Centric Residual RL for Zero-Shot Sim-to-Real VLA Enhancement Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:39:16.667380Z

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.

Observation c77a1dba-47d5-4595-acb3-0b2c299726d4 · inbound

Vision-Language-Action Models: Experimental Insights from a Real-World UR5 Platform cites this paper.

Vision-Language-Action Models: Experimental Insights from a Real-World UR5 Platform Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:34:45.891812Z

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.

Observation 5d47acb8-000c-4b07-a7c3-680fbe6df790 · inbound

Deep Reinforcement Learning for Individual Atomic Control and Cooling cites this paper.

Deep Reinforcement Learning for Individual Atomic Control and Cooling Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-01T12:45:44.040556Z

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.

Observation 8b16ae45-74be-4cf5-b641-1681d17c8011 · inbound

Efficient Sim-to-Real Transfer of World-Action Models from Synthetic Priors cites this paper.

Efficient Sim-to-Real Transfer of World-Action Models from Synthetic Priors Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:05:41.166264Z

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.

Observation ea0d028a-c360-4ee2-a97d-d250e2d02dee · inbound

Situation Aware Frontier Prioritization for Quadruped Search and Rescue cites this paper.

Situation Aware Frontier Prioritization for Quadruped Search and Rescue Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T04:31:57.980867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fef4e36-f209-47a4-b322-cd26cb020e99 · inbound

ResidencyRL: Reinforcement Learning in Simulated Clinical Environments cites this paper.

ResidencyRL: Reinforcement Learning in Simulated Clinical Environments Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:12.306957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.