Paper Citation Record · LEDGER

LLMs as Agentic Cooperative Players in Multiplayer UNO

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2509.09867.

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

pith.paper-citation-record.v1
2509.09867 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:35:39.627902Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

verified exact0
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e6c20f0-34ff-4990-af2d-bda6e00f2b73 · outbound

This paper cites Improving language understanding by generative pre-training,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Improving language understanding by generative pre-training,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.567607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01c6abd0-7af3-4f31-8623-e99afa258dc1 · outbound

This paper cites Language models are unsupervised multitask learners,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Language models are unsupervised multitask learners,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.571475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf6fd708-7f6e-44b2-a287-82fc694a3ca3 · outbound

This paper cites Language Models are Few-Shot Learners.

LLMs as Agentic Cooperative Players in Multiplayer UNO Language Models are Few-Shot Learners

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.574791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1cc0aa5-1d4e-45c3-8597-7357418c7a84 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Chain-of-thought prompting elicits reasoning in large language models,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.578272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e9bf81b-de90-4c45-9750-9e4a4a1a4fe3 · outbound

This paper cites How powerful are decoder-only transformer neural models?.

LLMs as Agentic Cooperative Players in Multiplayer UNO How powerful are decoder-only transformer neural models?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.582435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b556dbb1-2117-4446-a418-ee29e21330cc · outbound

This paper cites Language mod- els are few-shot learners,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Language mod- els are few-shot learners,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.585593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a7f2580-24f8-46aa-a5a7-7971b4e8e655 · outbound

This paper cites Palm: Scal- ing language modeling with pathways,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Palm: Scal- ing language modeling with pathways,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.588872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94357592-3e47-49d9-9894-b4a81c577647 · outbound

This paper cites RLCard: A Toolkit for Reinforcement Learning in Card Games.

LLMs as Agentic Cooperative Players in Multiplayer UNO RLCard: A Toolkit for Reinforcement Learning in Card Games

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.592352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23819ed2-45b3-474e-b8a3-642e033f5a15 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.595634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6a8e62a-b9b2-4aa1-b69c-6d6b45be1522 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.598524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96c77afa-1adb-4809-8b24-42bed31066c2 · outbound

This paper cites Do large language models learn human-like strategic preferences?.

LLMs as Agentic Cooperative Players in Multiplayer UNO Do large language models learn human-like strategic preferences?

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.601466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b31cbd29-3cf0-4d9e-bd38-6153b7627b63 · outbound

This paper cites Attention is all you need,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Attention is all you need,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.604200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8f0820d-83b9-4dae-bb86-30e6964777b7 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

LLMs as Agentic Cooperative Players in Multiplayer UNO Neural Machine Translation of Rare Words with Subword Units

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.607318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91db3df9-264a-43de-9aea-0f0f61d1309d · outbound

This paper cites Agents Play Thousands of 3D Video Games.

LLMs as Agentic Cooperative Players in Multiplayer UNO Agents Play Thousands of 3D Video Games

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.610856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43902b7a-3008-403a-a5ec-f9604c5647d9 · outbound

This paper cites Collaborative Quest Completion with LLM-driven Non-Player Characters in Minecraft.

LLMs as Agentic Cooperative Players in Multiplayer UNO Collaborative Quest Completion with LLM-driven Non-Player Characters in Minecraft

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.614241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c06f6a05-e9f7-4f29-b127-47fda500f60c · outbound

This paper cites PANGeA: Procedural Artificial Narrative using Generative AI for Turn-Based Video Games.

LLMs as Agentic Cooperative Players in Multiplayer UNO PANGeA: Procedural Artificial Narrative using Generative AI for Turn-Based Video Games

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.617712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dce3be0a-7698-418e-85e2-df0afd956c54 · outbound

This paper cites Chain of thought still thinks fast: Apricot helps with thinking slow,.

LLMs as Agentic Cooperative Players in Multiplayer UNO Chain of thought still thinks fast: Apricot helps with thinking slow,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.621647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f26874f3-b3fc-4700-a1f9-57a65ce093bd · outbound

This paper cites The base-rate effect on LLM benchmark performance: Disambiguating test-taking strategies from benchmark performance,.

LLMs as Agentic Cooperative Players in Multiplayer UNO The base-rate effect on LLM benchmark performance: Disambiguating test-taking strategies from benchmark performance,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.624696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23a82952-1c97-44f2-9880-d0e60a4187f0 · outbound

This paper cites an unresolved cited work.

LLMs as Agentic Cooperative Players in Multiplayer UNO Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T18:35:39.627902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.