Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.01103.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T21:01:24.818427Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T21:01:25.035901Z
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 b7a0d6c5-5c3a-4f94-8f68-20b3eb745ca9 · inbound
EvoCurr: Self-evolving Curriculum with Behavior Code Generation for Complex Decision-making cites this paper.
EvoCurr: Self-evolving Curriculum with Behavior Code Generation for Complex Decision-making Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
Reference 44
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T21:01:25.042474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d972127a-8bbc-48ec-b800-978408b73842 · inbound
Human-Like Goalkeeping in a Realistic Football Simulation: a Sample-Efficient Reinforcement Learning Approach cites this paper.
Human-Like Goalkeeping in a Realistic Football Simulation: a Sample-Efficient Reinforcement Learning Approach Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:03:21.434515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.