Paper Citation Record · LEDGER

Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2410.23426.

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

pith.paper-citation-record.v1
2410.23426 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:28:06.113517Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T07:12:41.449602Z

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 9ea93e69-0aa4-41da-a465-32a9c5798875 · inbound

Political-LLM: Large Language Models in Political Science cites this paper.

Political-LLM: Large Language Models in Political Science Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 264

Resolution: unresolved; no resolver link, observed 2026-08-11T19:52:04.947642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bafb63f-ebf0-47e8-a8d6-f4978d7beb87 · inbound

Large Language Models for Market Research: A Data-augmentation Approach cites this paper.

Large Language Models for Market Research: A Data-augmentation Approach Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-23T07:12:41.452993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ff233b39-6127-4542-8fa8-3c30441df661 · inbound

AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society cites this paper.

AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:12:30.931150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e343c437-54ff-4ace-a95c-e8426117e0a8 · inbound

Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond cites this paper.

Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T20:11:12.009821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cbd17f0-8047-491e-b264-9db8eb5a4cf3 · inbound

How Many Human Survey Respondents is a Large Language Model Worth? An Uncertainty Quantification Perspective cites this paper.

How Many Human Survey Respondents is a Large Language Model Worth? An Uncertainty Quantification Perspective Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:15:21.245425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9298555a-2767-46ca-bff6-991c86f93898 · inbound

LLM-Based Social Simulations Require a Boundary cites this paper.

LLM-Based Social Simulations Require a Boundary Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T18:28:06.113517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d81717b8-d9d4-4278-8b18-b0ee7e5d7a48 · inbound

LLMs are Introvert cites this paper.

LLMs are Introvert Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:13.291353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a71f11f6-a55e-4c75-a9c9-661e5e62f6d9 · inbound

Not There Yet: Evaluating Vision Language Models in Simulating the Visual Perception of People with Low Vision cites this paper.

Not There Yet: Evaluating Vision Language Models in Simulating the Visual Perception of People with Low Vision Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-05T20:19:33.207378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9e55d3c-e359-4d31-8d39-35cba6cede37 · inbound

The PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societies cites this paper.

The PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societies Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T14:31:29.446297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 34301ddc-1d6c-4a42-a988-7df6c04f4105 · inbound

Simulating Students with Large Language Models: A Review of Architecture, Mechanisms, and Role Modelling in Education with Generative AI cites this paper.

Simulating Students with Large Language Models: A Review of Architecture, Mechanisms, and Role Modelling in Education with Generative AI Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:08.110011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.