Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2304.06588.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T16:37:34.817466Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
159
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation e5212793-9c78-486d-ad0a-03105948806d · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 980645f7-5499-479a-af4d-577f75dc5645 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c76361e4-ae80-4c0c-95e4-8c7af174b32e · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f5e9a53-28fc-494a-b246-5746ac0c8b23 · inbound
Enterprise Large Language Model Evaluation Benchmark ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning
Reference 80
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 04e7cc53-d0fb-4a22-a6a7-203dd014290e · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 59040f85-48c5-497d-aad7-46160ca8301d · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f617e62e-2cc4-4c32-9390-477eee341451 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a997ae47-04f7-4bde-bc9f-b312b4f62381 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dcbc7af4-7396-47ac-af0c-8c98bf08cb4a · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c3e18d05-ae33-4a85-b2e2-3b3deade6c1a · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cdd42a81-dc21-4f0c-b279-ce48f839cdcd · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9b81af61-74fc-42d7-80ed-d8b60b979952 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cf2f500f-2cb7-43c8-9a70-655a262b25b7 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ec97abe6-6ddf-4082-8291-a5d586bc0eed · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 78bf5773-d8f4-45b6-88f9-c78d81a0c483 · inbound
Characterizing initial human-AI proof formalization workflows ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning
Reference 253
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 71c9f953-1e08-4f65-92da-dec7f852ef5a · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
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 ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning
Reference 22
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation bba0eb9c-0203-4792-9ecc-8639c8d81e69 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 11a9d015-ef43-4192-9396-9e85480a3d59 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c4e0194b-c49c-45a2-9e2c-3ec645098500 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f501d96-fc84-48d4-a778-600673394411 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.