Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PokerBench: Training Large Language Models to become Professional Poker Players
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2501.08328.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T21:58:47.021335Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T06:47:26.963289Z
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 5a36c371-5902-4b36-842f-dea470ce3499 · inbound
A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios cites this paper.
A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios PokerBench: Training Large Language Models to become Professional Poker Players
Reference 149
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:58:47.021335Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b5535ce-44fe-40b9-899e-abf9e06914ce · inbound
Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review cites this paper.
Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review PokerBench: Training Large Language Models to become Professional Poker Players
Reference 160
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:42:59.016494Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f49b6f6-5ae9-4788-8807-a56fc5849d5e · inbound
Think in Games: Learning to Reason in Games via Reinforcement Learning with Large Language Models cites this paper.
Think in Games: Learning to Reason in Games via Reinforcement Learning with Large Language Models PokerBench: Training Large Language Models to become Professional Poker Players
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:23:27.591640Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 72c368dc-84b8-4a7a-ac84-c65345189ef4 · inbound
Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse cites this paper.
Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse PokerBench: Training Large Language Models to become Professional Poker Players
Reference 227
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T03:26:19.145489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation bea6f925-331c-456f-86b6-3819f4cd963d · inbound
Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse cites this paper.
Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse PokerBench: Training Large Language Models to become Professional Poker Players
Reference 227
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T06:47:26.967716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.