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Paper Citation Record · LEDGER

Out of One, Many: Using Language Models to Simulate Human Samples

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2209.06899.

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

pith.paper-citation-record.v1
2209.06899 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:00:10.259911Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

92
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 89ed21fa-de56-4daa-9062-8a0a456295fb · inbound

Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators cites this paper.

Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators Out of One, Many: Using Language Models to Simulate Human Samples

Reference 137

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T11:13:04.763401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-12T11:13:04.597432Z digest=sha256:50ba7f12cf8b01ecb433fb96b3253339dec775dbf94d38adf8ab7aaad8cb0152

Observation 08569814-a49b-4695-92ac-52314cefb949 · inbound

The Effect of State Representation on LLM Agent Behavior in Dynamic Routing Games cites this paper.

The Effect of State Representation on LLM Agent Behavior in Dynamic Routing Games Out of One, Many: Using Language Models to Simulate Human Samples

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T00:00:10.259911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:00:10.259911Z digest=sha256:6a1d967cf5b5f8ae1612853be60f1bae9093ff6c51a18ea2b8d219738348702e

Observation 35f7564d-21c5-43ca-8562-1bda42a62b49 · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Out of One, Many: Using Language Models to Simulate Human Samples

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:02:52.708252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T22:02:36.307598Z digest=sha256:0b361117bb8d50edda80642eb8d5087cd9ede38b019bbd4dde0b6b5ab3f667b9

Observation 8d252832-0c1b-40d7-9b6f-5d17c5216f15 · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Out of One, Many: Using Language Models to Simulate Human Samples

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:20:32.027600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T08:18:18.448122Z digest=sha256:6756a9e75588a574d2ebee0dba03cc7eabd413700b5d4a1d7c3602280e1e4ce4

Observation 1dc092e8-19a5-4c9e-8f1b-fdf4e73f2bcc · inbound

Large Language Models as Virtual Survey Respondents: Evaluating Sociodemographic Response Generation cites this paper.

Large Language Models as Virtual Survey Respondents: Evaluating Sociodemographic Response Generation Out of One, Many: Using Language Models to Simulate Human Samples

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:46:44.890524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T18:46:39.488463Z digest=sha256:db6b32f4bd5f367c5f7d93db3a35400a92a0fb17b1a776a47f4e55fb8474a77d

Observation 49e55021-a66b-4e6f-b486-4047ed5adc78 · inbound

Human Label Variation as Stable Signal: Learning Annotator-Specific Explanation Behavior via Cross-Annotator Preference Optimization cites this paper.

Human Label Variation as Stable Signal: Learning Annotator-Specific Explanation Behavior via Cross-Annotator Preference Optimization Out of One, Many: Using Language Models to Simulate Human Samples

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T13:13:27.567995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T13:05:15.701729Z digest=sha256:3d8aa35417845bb36e37b74ba455c583b8e94f004345c5a2db663ae6b6f675fb

Observation b15607dd-0cba-4080-9451-de3354819a58 · inbound

Child-directed speech facilitates production, not comprehension, in BabyLMs cites this paper.

Child-directed speech facilitates production, not comprehension, in BabyLMs Out of One, Many: Using Language Models to Simulate Human Samples

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:06:14.341245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T17:28:32.405210Z digest=sha256:8439ada3d8d64a3a75f4caa19cd2d19e35fbab3e72da3ac48c2f7d1717af36e3

Observation 4e8f5077-fddd-4897-b525-268d49fd82b3 · inbound

Characterizing initial human-AI proof formalization workflows cites this paper.

Characterizing initial human-AI proof formalization workflows Out of One, Many: Using Language Models to Simulate Human Samples

Reference 218

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T04:06:34.889335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T09:29:50.282874Z digest=sha256:496a5bb13d6fcf1cbaaf388980a8989fa91acf83131bdd581c6fb4a8e19acbcb

Observation 587187d6-4c3f-4521-be65-6a1d979a0d6c · inbound

Marginal Alignment Does Not Guarantee Joint-Distribution Fidelity: An Official-Reference Audit of Nemotron-Personas-Korea with Cross-Locale Replication cites this paper.

Marginal Alignment Does Not Guarantee Joint-Distribution Fidelity: An Official-Reference Audit of Nemotron-Personas-Korea with Cross-Locale Replication Out of One, Many: Using Language Models to Simulate Human Samples

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T19:05:00.239029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-30T19:04:36.443335Z digest=sha256:fe66d8bbe98b7bd21259bde8a44a62c8903bda5d906dfef6e3c2c00b7a9c533a