Paper Citation Record · LEDGER

Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2312.05230.

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

pith.paper-citation-record.v1
2312.05230 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:37:54.762159Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T09:07:47.500221Z

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 e1d59946-47e9-4db9-882a-c7d54af66657 · inbound

AppAgent: Multimodal Agents as Smartphone Users cites this paper.

AppAgent: Multimodal Agents as Smartphone Users Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 83

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T10:16:43.806911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9554b66a-70e7-4096-bd5d-7752cc1f51d5 · inbound

Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions cites this paper.

Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-24T00:53:40.714824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making cites this paper.

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 275aa98d-c1ca-40be-af15-33ecba4d8c64 · inbound

GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control cites this paper.

GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T15:16:34.103629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0a0f822-9d42-4ef3-ae91-d83ad7d5572f · inbound

Mind Your Theory: Theory of Mind Goes Deeper Than Reasoning cites this paper.

Mind Your Theory: Theory of Mind Goes Deeper Than Reasoning Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T12:59:38.625624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0482f92-de92-4b0b-832f-23516f727d1b · inbound

When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning? cites this paper.

When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning? Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:42:13.486462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ecf2858b-dc5e-4b53-8e0d-12c503eec292 · inbound

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems cites this paper.

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 218

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:42:10.844949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7228a10a-50bd-4ee2-8124-55c720d241bb · inbound

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact cites this paper.

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 123

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:11.165507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6818f7d3-cbc4-4923-97b5-a6c507ebe51b · inbound

LLM world models are mental: Output layer evidence of brittle world model use in LLM mechanical reasoning cites this paper.

LLM world models are mental: Output layer evidence of brittle world model use in LLM mechanical reasoning Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T15:32:47.959750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc0791f7-6ea3-4a4d-b0f7-0fc25bf3fbd9 · inbound

Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts cites this paper.

Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-06T14:22:31.527546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b6dc75d-4fe8-42df-a50c-b97eac9edd8b · inbound

General Agentic Planning Through Simulative Reasoning with World Models cites this paper.

General Agentic Planning Through Simulative Reasoning with World Models Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-22T12:41:33.543983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 00bf679d-24d9-445f-96e0-482a6690a4f6 · inbound

A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems cites this paper.

A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T23:21:42.446269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation eb3636f9-968d-4c22-9767-75928a0264f0 · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 206

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:05:31.623402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 76f67060-5627-46b4-a749-85fd7ceca4d4 · inbound

Memory in the Age of AI Agents cites this paper.

Memory in the Age of AI Agents Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 176

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T18:18:20.537343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 75e3aef3-1080-4c84-a432-6fbca08f3f73 · inbound

Toward World Modeling of Physiological Signals with Chaos-Theoretic Balancing and Latent Dynamics cites this paper.

Toward World Modeling of Physiological Signals with Chaos-Theoretic Balancing and Latent Dynamics Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-19T15:07:37.047540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f7065e5d-c6c5-4321-bc0d-b3fbb30ef75f · inbound

Efficient Agentic Reasoning Through Self-Regulated Simulative Planning cites this paper.

Efficient Agentic Reasoning Through Self-Regulated Simulative Planning Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:34:40.977520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 817cd248-ed54-496c-81a1-ff90a74da390 · inbound

Building Social World Models with Large Language Models cites this paper.

Building Social World Models with Large Language Models Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 101

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:07:47.505343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6cebd073-3be4-493b-93c7-0fea92ea8074 · inbound

Computational Humor with Multimodal LLMs: Methods, Datasets, Evaluation, and Challenges cites this paper.

Computational Humor with Multimodal LLMs: Methods, Datasets, Evaluation, and Challenges Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T15:37:54.762159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.