Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.02081.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:58:35.506929Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T04:39:35.242876Z
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 7112ff02-0314-46cb-b8c2-f6052cbe6ec2 · inbound
Artificial Generals Intelligence: Mastering Generals.io with Reinforcement Learning cites this paper.
Artificial Generals Intelligence: Mastering Generals.io with Reinforcement Learning FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:58:35.506929Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 980b4196-b9ca-4a6f-98d2-893136c763b3 · inbound
PillagerBench: Benchmarking LLM-Based Agents in Competitive Minecraft Team Environments cites this paper.
PillagerBench: Benchmarking LLM-Based Agents in Competitive Minecraft Team Environments FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:58:44.926494Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b64ba5e-dfb8-4f53-b30a-451d65d807ff · inbound
Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest cites this paper.
Cooperate to Compete: Strategic Coordination in Multi-Agent Conquest FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Reference 17
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T23:36:36.068705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1d208a03-7989-4010-852c-00efe563d889 · inbound
Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning cites this paper.
Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:16:09.384027Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2fc616cf-2c23-48d9-a930-cdacee64eb15 · inbound
For How Long Should We Be Punching? Learning Action Duration in Fighting Games cites this paper.
For How Long Should We Be Punching? Learning Action Duration in Fighting Games FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:39:35.244579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.