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Paper Citation Record · LEDGER

Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2502.20897.

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

pith.paper-citation-record.v1
2502.20897 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:28:06.188249Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T14:36:06.626337Z

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 33dc239e-c2c0-4683-994a-15ab734c4a05 · inbound

SubData: Bridging Heterogeneous Datasets to Enable Theory-Driven Evaluation of Political and Demographic Perspectives in LLMs cites this paper.

SubData: Bridging Heterogeneous Datasets to Enable Theory-Driven Evaluation of Political and Demographic Perspectives in LLMs Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T10:19:33.696834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:19:33.696834Z digest=sha256:07b8488e145a3d22bc2219a97292acd66ad272f321f728f5ff656fdb00183b5c

Observation 13184cf0-eb8e-4b6e-9b28-6bc5ead11132 · inbound

Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning cites this paper.

Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:54:16.877850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:54:16.877850Z digest=sha256:3c8aaa9d30cd801be6a96bcadb4925077325a35635409ee2b3ce24494ef557bb

Observation b74c46c8-54a9-40ec-9d5c-9acd7ad7b75a · inbound

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

LLM-Based Social Simulations Require a Boundary Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T18:28:06.188249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:28:06.188249Z digest=sha256:89f8c349d473c9983e0ea6a868db7ef6ac318ae3fadd77bc6f80be042a07a1d8

Observation af03a872-9f6f-4631-8c36-a917dc2b3d5e · inbound

Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models cites this paper.

Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T17:08:16.729891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:08:16.729891Z digest=sha256:70bb21bf516e03f3d452ef5fbd2c5dcaa004a98f6b5dc9c1de9c23eeba2ac38a

Observation ed29df5c-ed53-4b11-b6c7-79b3552e6eed · inbound

Fine-Grained Perspectives: Modeling Explanations with Annotator-Specific Rationales cites this paper.

Fine-Grained Perspectives: Modeling Explanations with Annotator-Specific Rationales Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:36:06.635356Z

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.

source=arxiv_source observed=2026-05-09T21:27:53.611866Z digest=sha256:3ac94361656dfdfdb611be8a5d3b7a802a17f4445f8733d2918fb90d100efee2