Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Robot Trains Robot: Automatic Real-World Policy Adaptation and Learning for Humanoids
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2508.12252.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-03T12:40:11.283716Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T12:48:11.092966Z
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 ea9dacbd-33d9-400b-a4dd-ea8d845c60b7 · inbound
Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation cites this paper.
Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation Robot Trains Robot: Automatic Real-World Policy Adaptation and Learning for Humanoids
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T23:06:21.288640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d1a1e7ef-d564-4433-a598-c3b7b16ba780 · inbound
FADA: Few-Shot Domain Adaptation via Dynamics Alignment for Humanoid Control cites this paper.
FADA: Few-Shot Domain Adaptation via Dynamics Alignment for Humanoid Control Robot Trains Robot: Automatic Real-World Policy Adaptation and Learning for Humanoids
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T15:25:48.479963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d5dff37c-69d6-4fb0-bded-f9c65388aa07 · inbound
One Demonstration Is Enough for Real-World Robotic Reinforcement Learning cites this paper.
One Demonstration Is Enough for Real-World Robotic Reinforcement Learning Robot Trains Robot: Automatic Real-World Policy Adaptation and Learning for Humanoids
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T12:48:11.094715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.