Paper Citation Record · LEDGER

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment

As of 10 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 4 inbound Pith citation observations for arXiv:2506.06355.

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

pith.paper-citation-record.v1
2506.06355 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:32:35.968884Z

measured 62 of 62 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:48:46.854749Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:06:20.253908Z

Reference resolution

58 of 58 outbound references displayed

verified exact6
verified fuzzy6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 51e5dedc-0255-4b41-bd87-7254c2958e34 · outbound

This paper cites online" 'onlinestring :=.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment online" 'onlinestring :=

Reference 1

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This paper cites write newline.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment write newline

Reference 2

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Observation f8d89e4a-7bb0-48d8-8a5c-fd5a0c42aa30 · outbound

This paper cites https://www.census.gov/programs-surveys/acs/ American community survey (acs).

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment https://www.census.gov/programs-surveys/acs/ American community survey (acs)

Reference 3

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Observation f1d45142-4991-4986-95f6-286f90d0bdb4 · outbound

This paper cites GPT-4 Technical Report.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment GPT-4 Technical Report

Reference 4

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 5

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This paper cites did you feel it?.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment did you feel it?

Reference 6

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 7

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 8

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 9

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 10

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Observation e1b50853-e204-44b5-864d-d581fed0823b · outbound

This paper cites When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?

Reference 11

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 12

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Observation d44d1635-d626-49da-bf26-e9c70598afc0 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 13

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Reasoning with Language Model is Planning with World Model

Reference 14

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Observation 680414ce-b1e3-4075-b479-7c6a1a2db578 · outbound

This paper cites Large Language Models in Fire Engineering: An Examination of Technical Questions Against Domain Knowledge.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Large Language Models in Fire Engineering: An Examination of Technical Questions Against Domain Knowledge

Reference 15

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Reference 16

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 17

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 18

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Observation 475ed641-c54b-4578-900e-d14b2eaeb85a · outbound

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 19

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 20

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 21

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 22

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 24

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Observation ab07452c-ccf6-4360-968a-41cf88f8909e · outbound

This paper cites From System 1 to System 2: A Survey of Reasoning Large Language Models.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment From System 1 to System 2: A Survey of Reasoning Large Language Models

Reference 25

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 26

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This paper cites Towards Democratized Flood Risk Management: An Advanced AI Assistant Enabled by GPT-4 for Enhanced Interpretability and Public Engagement.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Towards Democratized Flood Risk Management: An Advanced AI Assistant Enabled by GPT-4 for Enhanced Interpretability and Public Engagement

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 36

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Geological Survey

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Geological Survey

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Observation 43c51355-7754-40ee-a5d0-a64cf5515ee0 · outbound

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Reference 44

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Observation 9e62ce1f-e201-4751-a5b1-57f18f4f79d7 · outbound

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 45

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Observation 4d8c8fb3-f061-4138-89f4-969d90da329d · outbound

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 46

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Observation 1d4973d9-5e33-4547-bed7-df496298719d · outbound

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought

Reference 47

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LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 48

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This paper cites OpenCity: A Scalable Platform to Simulate Urban Activities with Massive LLM Agents.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment OpenCity: A Scalable Platform to Simulate Urban Activities with Massive LLM Agents

Reference 49

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Observation d4c5c0cd-0860-4158-bdfc-d55305e017b4 · outbound

This paper cites LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models

Reference 50

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This paper cites Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data

Reference 51

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Unavailable: canonical work link unavailable.

Observation fd186912-810c-4e4b-a4bb-b44001cb2a61 · outbound

This paper cites Sparrow: Data-Efficient Video-LLM with Text-to-Image Augmentation.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Sparrow: Data-Efficient Video-LLM with Text-to-Image Augmentation

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:32:36.551624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a0df9252-19f5-49d9-8eac-3a2d914f7646 · outbound

This paper cites an unresolved cited work.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:32:38.138509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 10f8a6b1-f3ab-418c-85e7-adcca51a028a · outbound

This paper cites an unresolved cited work.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:32:37.992646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4046ffb0-29a4-4f87-9da5-7164044d29e3 · outbound

This paper cites Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T11:32:35.603955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8d0a408-e5c7-4019-a376-6d81578cf884 · outbound

This paper cites an unresolved cited work.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:32:37.815607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5bc259d7-b55a-4044-be47-dfdcbeb9b082 · outbound

This paper cites an unresolved cited work.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T11:32:35.834624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e608f13-38de-4481-b0dc-91f339e84338 · outbound

This paper cites an unresolved cited work.

LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:32:37.542378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation 1165b6be-d56c-4bad-89bf-b19dff4bec53 · inbound

From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models cites this paper.

From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:50:47.265820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5a2fa18f-591d-4707-847e-ad01ebdddd27 · inbound

Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response cites this paper.

Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-18T07:56:04.150182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a290b97f-d1bf-41af-bd0c-27a9722f729d · inbound

Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View cites this paper.

Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T23:06:20.255545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6d1b634b-c1e5-42b5-9af9-cb631b29c750 · inbound

An Agentic Interface for End-to-End Probabilistic Seismic Hazard and Risk Analysis cites this paper.

An Agentic Interface for End-to-End Probabilistic Seismic Hazard and Risk Analysis LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T09:48:46.854749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.