Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fine-Tuning Hard-to-Simulate Objectives for Quadruped Locomotion: A Case Study on Total Power Saving
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.10956.
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 2026-08-05T12:16:02.227554Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T22:00:41.943683Z
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 aeca78b1-92ce-4985-968a-5468ee04e1f0 · inbound
Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control cites this paper.
Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control Fine-Tuning Hard-to-Simulate Objectives for Quadruped Locomotion: A Case Study on Total Power Saving
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:16:02.227554Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2fd9a96a-e2d7-4846-810e-ec414f6b45e1 · inbound
TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance cites this paper.
TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance Fine-Tuning Hard-to-Simulate Objectives for Quadruped Locomotion: A Case Study on Total Power Saving
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T22:00:41.946890Z
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.