Paper Citation Record · LEDGER

ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2304.06588.

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

pith.paper-citation-record.v1
2304.06588 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:15:05.010781Z

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
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External citation measurements

159
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 cff35308-7bd3-4bbb-9726-da73e6c3c15c · inbound

Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness cites this paper.

Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 42

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Source-reported events for the cited work

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Observation 70da9379-aecf-4ac8-9e21-9629d663b7bf · inbound

The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection cites this paper.

The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T19:02:14.538798Z

Source-reported events for the cited work

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Observation 8d62b43c-6f80-44e2-92a3-a88959221959 · inbound

Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments cites this paper.

Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T05:32:20.889570Z

Source-reported events for the cited work

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Observation e5212793-9c78-486d-ad0a-03105948806d · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 225

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:08:35.479171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1b2b6d60-95d9-4c75-bfbe-2ef55151f5b7 · inbound

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

Political-LLM: Large Language Models in Political Science ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T19:52:03.909656Z

Source-reported events for the cited work

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Observation 5991f959-9497-413c-870f-19a85dad82be · inbound

Labeling NIDS Rules with MITRE ATT&CK Techniques: Machine Learning vs. Large Language Models cites this paper.

Labeling NIDS Rules with MITRE ATT&CK Techniques: Machine Learning vs. Large Language Models ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T15:28:37.797060Z

Source-reported events for the cited work

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Observation a770aa8a-e288-435a-b11f-998e033bec83 · inbound

Nano-ESG: Extracting Corporate Sustainability Information from News Articles cites this paper.

Nano-ESG: Extracting Corporate Sustainability Information from News Articles ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T11:41:38.559605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dbc1498-c00f-41e3-afe3-d482511669f9 · inbound

From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysis cites this paper.

From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysis ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 11

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Source-reported events for the cited work

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Observation ebeb0486-5a8e-49d0-a01a-5d262108f76a · inbound

From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis cites this paper.

From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-09T20:46:46.241771Z

Source-reported events for the cited work

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Observation 16e33d5d-777f-410d-9d12-bcdbb20b1e38 · inbound

Concept Navigation and Classification via Open-Source Large Language Model Processing cites this paper.

Concept Navigation and Classification via Open-Source Large Language Model Processing ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T21:39:46.025853Z

Source-reported events for the cited work

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Observation 10260a13-2b83-484f-a1f7-109376bdedc8 · inbound

Aligning Black-box Language Models with Human Judgments cites this paper.

Aligning Black-box Language Models with Human Judgments ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 35

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Source-reported events for the cited work

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Observation 980645f7-5499-479a-af4d-577f75dc5645 · inbound

Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy cites this paper.

Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T16:37:34.817466Z

Source-reported events for the cited work

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Observation 0f88b318-5cf1-432a-9071-aad087484c4c · inbound

Comparing LLM Text Annotation Skills: A Study on Human Rights Violations in Social Media Data cites this paper.

Comparing LLM Text Annotation Skills: A Study on Human Rights Violations in Social Media Data ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T21:15:05.010781Z

Source-reported events for the cited work

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Observation c76361e4-ae80-4c0c-95e4-8c7af174b32e · inbound

Contrastive Learning on LLM Back Generation Treebank for Cross-domain Constituency Parsing cites this paper.

Contrastive Learning on LLM Back Generation Treebank for Cross-domain Constituency Parsing ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 39

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Source-reported events for the cited work

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Observation 8f5e9a53-28fc-494a-b246-5746ac0c8b23 · inbound

Enterprise Large Language Model Evaluation Benchmark cites this paper.

Enterprise Large Language Model Evaluation Benchmark ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T22:56:36.982426Z

Source-reported events for the cited work

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Observation 04e7cc53-d0fb-4a22-a6a7-203dd014290e · inbound

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents cites this paper.

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 55

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Source-reported events for the cited work

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Observation 59040f85-48c5-497d-aad7-46160ca8301d · inbound

Reliable Annotations with Less Effort: Evaluating LLM-Human Collaboration in Search Clarifications cites this paper.

Reliable Annotations with Less Effort: Evaluating LLM-Human Collaboration in Search Clarifications ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:35.155795Z

Source-reported events for the cited work

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Observation f617e62e-2cc4-4c32-9390-477eee341451 · inbound

Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification cites this paper.

Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 37

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Observation a997ae47-04f7-4bde-bc9f-b312b4f62381 · inbound

Using AI to replicate human experimental results: a motion study cites this paper.

Using AI to replicate human experimental results: a motion study ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 11

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Observation dcbc7af4-7396-47ac-af0c-8c98bf08cb4a · 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 ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:46:44.982483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c3e18d05-ae33-4a85-b2e2-3b3deade6c1a · inbound

The Shrinking Lifespan of LLMs in Science cites this paper.

The Shrinking Lifespan of LLMs in Science ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:16:08.002342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cdd42a81-dc21-4f0c-b279-ce48f839cdcd · inbound

SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models cites this paper.

SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:55:20.889485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9b81af61-74fc-42d7-80ed-d8b60b979952 · inbound

Evaluating LLMs as Human Surrogates in Controlled Experiments cites this paper.

Evaluating LLMs as Human Surrogates in Controlled Experiments ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:41:07.380401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cf2f500f-2cb7-43c8-9a70-655a262b25b7 · inbound

Assessing Capabilities of Large Language Models in Social Media Analytics: A Multi-task Quest cites this paper.

Assessing Capabilities of Large Language Models in Social Media Analytics: A Multi-task Quest ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ec97abe6-6ddf-4082-8291-a5d586bc0eed · inbound

Interpretable Discriminative Text Representations via Agreement and Label Disentanglement cites this paper.

Interpretable Discriminative Text Representations via Agreement and Label Disentanglement ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:49:41.165714Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Human agency in initial human-AI proof formalization workflows cites this paper.

Human agency in initial human-AI proof formalization workflows ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 253

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T09:31:48.843176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9177b4bc-02d2-4e39-a9ea-66f2121539a6 · inbound

What Prediction Markets Can See: Market Formation, Settlement Legibility, and the Geography of Tradable Uncertainty in Africa and Latin America cites this paper.

What Prediction Markets Can See: Market Formation, Settlement Legibility, and the Geography of Tradable Uncertainty in Africa and Latin America ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:08:43.282965Z

Source-reported events for the cited work

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Observation 71c9f953-1e08-4f65-92da-dec7f852ef5a · inbound

Improving Medical Communication using Rubric-Guided Counterfactual Recommendations cites this paper.

Improving Medical Communication using Rubric-Guided Counterfactual Recommendations ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:49:18.384689Z

Source-reported events for the cited work

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Observation 27e892b8-5115-49c5-a927-af038d0a724d · inbound

The Model as One Rater Among Several: Measuring Political Positions in Data-Sparse Regions with a Language-Model Panel cites this paper.

The Model as One Rater Among Several: Measuring Political Positions in Data-Sparse Regions with a Language-Model Panel ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:39:49.403028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bba0eb9c-0203-4792-9ecc-8639c8d81e69 · inbound

Structure Before Collapse: Transient semantic geometry in next-token prediction cites this paper.

Structure Before Collapse: Transient semantic geometry in next-token prediction ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 99

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:29:51.175154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 11a9d015-ef43-4192-9396-9e85480a3d59 · inbound

Using AI Agents to Automate Black-Box Audits of Personalization Algorithms at Scale cites this paper.

Using AI Agents to Automate Black-Box Audits of Personalization Algorithms at Scale ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-07-01T12:15:43.420459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Demographic Prompting at Scale: When More Attributes Hurt LLM--Human Agreement cites this paper.

Demographic Prompting at Scale: When More Attributes Hurt LLM--Human Agreement ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 54

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Observation 5f501d96-fc84-48d4-a778-600673394411 · inbound

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering cites this paper.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T19:12:13.721189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.