Paper Citation Record · LEDGER

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making

As of 23 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2411.15998.

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

pith.paper-citation-record.v1
2411.15998 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:43:44.588632Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-14T19:57:28.642081Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T19:57:53.008216Z

Reference resolution

37 of 37 outbound references displayed

verified exact0
verified fuzzy5
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b0c882e-d921-430d-acd9-f47e4e404a7f · outbound

This paper cites Reasoning with Language Model is Planning with World Model.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Reasoning with Language Model is Planning with World Model

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:43.538194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca4b6103-6783-427f-b524-e55acf297f8d · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Tree of thoughts: Deliberate problem solving with large language models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:43.586527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38222d46-6499-466d-86a7-580a2bee91ee · outbound

This paper cites Large language models as commonsense knowledge for large-scale task planning.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Large language models as commonsense knowledge for large-scale task planning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:45.112547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ad0b0a45-03de-44ed-b7bc-04ec3f964834 · outbound

This paper cites Monte carlo sampling for regret minimization in extensive games.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Monte carlo sampling for regret minimization in extensive games

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:45.096714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2f74efab-e0ac-4416-8729-31d176cd8665 · outbound

This paper cites Goofspiel—the game of pure strategy.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Goofspiel—the game of pure strategy

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:45.081083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ea4ab028-eb46-4ad0-9fa6-33e784e8742c · outbound

This paper cites Self-refine: Iterative refinement with self-feedback.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Self-refine: Iterative refinement with self-feedback

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:43.810390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea0e2c91-cddc-48b7-9270-99fa402606f2 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:43.818224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce9a996d-2914-42f5-8a99-a4e07993ed8b · outbound

This paper cites Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:43.822759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6f93e22-c972-440d-9ba0-b103cb32df81 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making On the Opportunities and Risks of Foundation Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:43.874871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01c4e971-62ba-46f1-be72-9a1249272b6d · outbound

This paper cites an unresolved cited work.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:43:45.046986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 78e3d0fc-a454-4fc2-8684-34fe8764da5b · outbound

This paper cites an unresolved cited work.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.016023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43a2232d-0cd7-4c6d-8384-836b36067e2a · outbound

This paper cites Emergent Abilities of Large Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Emergent Abilities of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.021976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b47e2153-3a4f-4897-aa80-5d321b527486 · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making PaLM: Scaling Language Modeling with Pathways

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.069372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb1ce79f-e34d-48be-aace-4a0cba00ccd9 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Scaling Instruction-Finetuned Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.118159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9890aa8-e90f-4f8e-8081-f97447c54b5c · outbound

This paper cites KoLA: Carefully Benchmarking World Knowledge of Large Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making KoLA: Carefully Benchmarking World Knowledge of Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.146259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afb0d613-9220-438f-af83-d41e1f937224 · outbound

This paper cites A survey on large language model based autonomous agents.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making A survey on large language model based autonomous agents

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:45.022698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 162821ce-f19b-4af0-9db0-a84c690985db · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making ReAct: Synergizing Reasoning and Acting in Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.155461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84ede876-d799-421b-8bb9-71c4d51a97b0 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.160285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 368e6985-d7e8-4b53-8466-68fdab63c874 · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.254195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb491abc-5bbe-405d-9dad-d4d71e8a17c3 · outbound

This paper cites Generative Agents: Interactive Simulacra of Human Behavior.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Generative Agents: Interactive Simulacra of Human Behavior

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.365453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2b9ff32-3dd6-46dd-abb0-92ca366799cc · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Toolformer: Language models can teach themselves to use tools

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.378143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57b23c19-bc45-4597-a160-b4ef21cda2ac · outbound

This paper cites Large Language Models as Tool Makers.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Large Language Models as Tool Makers

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.383545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20edc0cf-3a9a-48c5-a596-1b0cf28bed22 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.388112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de67268e-3c7c-4f17-bc42-8908d63fda50 · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Graph of thoughts: Solving elaborate problems with large language models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.392750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b33480d0-05a8-4eed-b71b-ca1648b4c7e7 · outbound

This paper cites Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.397366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e3f1647-f637-4be7-b120-16ab252df1f4 · outbound

This paper cites Leveraging pre-trained large language models to construct and utilize world models for model-based task planning.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Leveraging pre-trained large language models to construct and utilize world models for model-based task planning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.428090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7645cd5e-ad11-44b8-8dc5-db8d4b2aa4a2 · outbound

This paper cites Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.467524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b8a6671-11a5-4d16-bbcb-9d3b965cbbe1 · outbound

This paper cites CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.542891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be6b53de-7adb-4479-b91d-c08d0b8207f3 · outbound

This paper cites Expel: Llm agents are experiential learners.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Expel: Llm agents are experiential learners

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.550585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46d712ec-dd39-4cf2-aed6-eb17f9577512 · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.555592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc6d9f2d-48de-4635-a607-70d547252ef2 · outbound

This paper cites Language to Rewards for Robotic Skill Synthesis.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Language to Rewards for Robotic Skill Synthesis

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.561260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b09fb152-41f9-4892-a2f3-7b47440a957c · outbound

This paper cites Mastering the game of go without human knowledge.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Mastering the game of go without human knowledge

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.566422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6699ac5c-fd7d-463a-9757-63e33dd6e6a6 · outbound

This paper cites Mastering atari, go, chess and shogi by planning with a learned model.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Mastering atari, go, chess and shogi by planning with a learned model

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.571043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af434a38-ff5b-4dd3-af24-c6b4c789e5fe · outbound

This paper cites Human-level play in the game of diplomacy by combining language models with strategic reasoning.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Human-level play in the game of diplomacy by combining language models with strategic reasoning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.576045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7106c292-d144-4a14-84be-dd224f8c855f · outbound

This paper cites Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.580193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f45de332-411c-4393-87f4-47494ee8d054 · outbound

This paper cites Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T13:43:44.584395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc35932e-76fd-4586-a27f-16f4c07c1be2 · outbound

This paper cites State␣must␣be␣an␣instance␣of␣HiddenState.

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making State␣must␣be␣an␣instance␣of␣HiddenState

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:43:44.938409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 188fa228-d05f-43f1-a5f4-0a4cc1ff0956 · inbound

Learning POMDP World Models from Observations with Language-Model Priors cites this paper.

Learning POMDP World Models from Observations with Language-Model Priors PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:57:53.011851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.