Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.06687.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:24:59.961027Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T16:56:07.747463Z
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 1bfd96f7-721e-46bc-821e-f6528fd842e8 · inbound
Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One cites this paper.
Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:24:59.961027Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 85bba71d-bfa2-4543-b947-d32463ec5e82 · inbound
Uncertainty-aware Reward Design Process cites this paper.
Uncertainty-aware Reward Design Process Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics
Reference 2012
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:39:14.628984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ed27b09-9f3c-49ab-9504-2c39f3a129f0 · inbound
Model-Based Proactive Cost Generation for Learning Safe Policies Offline with Limited Violation Data cites this paper.
Model-Based Proactive Cost Generation for Learning Safe Policies Offline with Limited Violation Data Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:56:07.753921Z
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.