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Paper Citation Record · LEDGER

Building a 3-Player Mahjong AI using Deep Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2202.12847.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2202.12847 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:06:19.725355Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-21T05:39:40.959222Z

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 f96a14bd-9a50-4777-b947-e6bf8a364368 · inbound

Evolutionary Optimization of Deep Learning Agents for Sparrow Mahjong cites this paper.

Evolutionary Optimization of Deep Learning Agents for Sparrow Mahjong Building a 3-Player Mahjong AI using Deep Reinforcement Learning

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T22:06:19.725355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:06:19.725355Z digest=sha256:1a03acf6a04d789f5c1e90da998266a1e4b873004361a2969ca88a7e19a534fd

Observation 91604b0d-7d36-4d74-b681-6418c006152b · inbound

Mahjax: A GPU-Accelerated Mahjong Simulator for Reinforcement Learning in JAX cites this paper.

Mahjax: A GPU-Accelerated Mahjong Simulator for Reinforcement Learning in JAX Building a 3-Player Mahjong AI using Deep Reinforcement Learning

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:39:40.961183Z

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.

source=pdf_text observed=2026-05-21T05:35:27.427721Z digest=sha256:d5b1e0b37a9b2466bc7af372ac18822ad4990d4fc40f95c204045f7079c2688c