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Paper Citation Record · LEDGER

Understanding Domain Randomization for Sim-to-real Transfer

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2110.03239.

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

pith.paper-citation-record.v1
2110.03239 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:30:08.728361Z

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
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

33
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 3d9c91d8-8be8-4684-a205-42a6b4d56cba · inbound

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills cites this paper.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Understanding Domain Randomization for Sim-to-real Transfer

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.728361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.728361Z digest=sha256:a9a0e2c5b176b360a0a9f4c70add35e6776678d9d554e921aebb7f2d8242d9a7

Observation 3a499f1f-455f-4ea9-9bdc-324eb9e0df8f · inbound

Humans Coexist, So Must Embodied Artificial Agents cites this paper.

Humans Coexist, So Must Embodied Artificial Agents Understanding Domain Randomization for Sim-to-real Transfer

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-08T21:27:27.351890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:27:27.351890Z digest=sha256:c0021636cc4ba28ca8c7cc9ceee717683fb2d4d767516a88ebf7046466fc78eb

Observation df52e767-143e-4f50-bdb3-099563a1177d · inbound

Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation cites this paper.

Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation Understanding Domain Randomization for Sim-to-real Transfer

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T00:05:05.612989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:05:05.612989Z digest=sha256:3d005948321d1b888ec66d5646d45476cafe986d50833ea273d929953666bda3

Observation 37744985-66d8-45c9-87c4-27bdddde1692 · inbound

McARL:Morphology-Control-Aware Reinforcement Learning for Generalizable Quadrupedal Locomotion cites this paper.

McARL:Morphology-Control-Aware Reinforcement Learning for Generalizable Quadrupedal Locomotion Understanding Domain Randomization for Sim-to-real Transfer

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:36:25.255118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:36:25.255118Z digest=sha256:7fd7606bb1fd1bd193eb670e043230d16a9f8eaca88d406d456728fd94e6f341

Observation 924fea50-4cd8-4b30-a670-70c94db900cf · inbound

Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning cites this paper.

Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning Understanding Domain Randomization for Sim-to-real Transfer

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:37:23.614328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:37:23.614328Z digest=sha256:d79973f7c5e80c4094f69192bb19696e6688e1e4b2f6ef153fe6c5602e9dafaa

Observation 184933b4-ad98-4aa4-9e17-61c4260a859c · inbound

Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control cites this paper.

Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control Understanding Domain Randomization for Sim-to-real Transfer

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T12:38:13.189222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:38:13.189222Z digest=sha256:77c74b27eb6084de84aba76cec531fc48eefab68c5b51980aa10d24b03438878

Observation 2009e78b-d955-4f6f-9cd1-9bb7442976db · inbound

Foundation Model Driven Robotics: A Comprehensive Review cites this paper.

Foundation Model Driven Robotics: A Comprehensive Review Understanding Domain Randomization for Sim-to-real Transfer

Reference 154

Resolution
unresolved
no resolver link, observed 2026-08-06T17:43:53.406311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:43:53.406311Z digest=sha256:9fc12252a2e8a569de1eadd61c58fd487c9716182aa88cdbf57649d2e8612faa

Observation 23ab09ef-081e-4601-9436-5eee88753e02 · inbound

Simulation Priors for Data-Efficient Deep Learning cites this paper.

Simulation Priors for Data-Efficient Deep Learning Understanding Domain Randomization for Sim-to-real Transfer

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T05:10:10.464051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:10:10.464051Z digest=sha256:94b0a7af9059e88edea5c7deba4b59a4d294c4049a84bd1e8dbbdaa56aee355c

Observation 50c439eb-c5b9-487f-904e-167a0bf2be08 · inbound

Now You See That: Learning End-to-End Humanoid Locomotion from Raw Pixels cites this paper.

Now You See That: Learning End-to-End Humanoid Locomotion from Raw Pixels Understanding Domain Randomization for Sim-to-real Transfer

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:27:32.276563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T07:23:03.673259Z digest=sha256:fd473115bf784bf11dca094d903aef763a409a0ee39634d4353f268e80eaa0f4

Observation d507f494-150f-4340-ab7d-3c376256c195 · inbound

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift cites this paper.

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift Understanding Domain Randomization for Sim-to-real Transfer

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:21:25.363159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T03:27:41.845716Z digest=sha256:ec112eef42f73529ba75f3107418405e9bed27fb804a6ae9f3f2c0059660bf28

Observation e05c8b8e-6ca9-4fac-9f07-22cb94ab18db · inbound

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift cites this paper.

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift Understanding Domain Randomization for Sim-to-real Transfer

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:09:07.637572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T22:04:57.245024Z digest=sha256:b4b5b57ee1f67623a890c0ad747fdabf43fcc712222142ddd741e51d891dd10b

Observation e244d894-13ab-4d21-a3f3-5237656e0b4c · inbound

Zero-shot Transfer of Reinforcement Learning Control Policies for the Swing-Up and Stabilization of a Cart-Pole System cites this paper.

Zero-shot Transfer of Reinforcement Learning Control Policies for the Swing-Up and Stabilization of a Cart-Pole System Understanding Domain Randomization for Sim-to-real Transfer

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-06-26T11:39:24.549635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T11:39:18.595140Z digest=sha256:ef5bb6c73302cc10b6acdd55d8ed4893b528e3a6d337590c70511dc145e6bb89

Observation fbee72d6-5f5b-476f-bd3c-cf51bdb56969 · inbound

Stationary Robust Mean-Field Games under Model Mismatches cites this paper.

Stationary Robust Mean-Field Games under Model Mismatches Understanding Domain Randomization for Sim-to-real Transfer

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:49:42.733940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T10:50:40.841967Z digest=sha256:c758f84a9c16a902d5b6a966d38174848552918a51d4a0d6fed80ea8741e2ed2