Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T12:26:42.235753Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2412.14276.
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, observed 2026-08-11T12:26:42.235753Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
83 of 83 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 40fc0382-eb01-4c30-9767-cab896e2854f · outbound
Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data International Journal of Data Science and Analytics 13, 335–362 (2022) https://doi.org/10.1007/s41060-021-00302-z
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data Large Language Models for Data Annotation and Synthesis: A Survey
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data In: 2022 Interna- tional Conference on Informatics Electrical and Electronics (ICIEE), pp
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data ACM Computing Surveys 53 (2020) https://doi
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data Journal of economic perspectives 31(2), 211–236 (2017)
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data In: 2022 13th International Conference on Computing Communication and Net- working Technologies (ICCCNT), pp
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data In: 2019 IEEE International Conference on Data Mining (ICDM), pp
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data Heliyon9(10) (2023) https://doi.org/10.1016/j.heliyon.2023.e20382
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data Expert Systems with Applications 158, 113503 (2020)
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data Unresolved cited work
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data Multimedia Tools and Applications 82 (2022) https://doi.org/10.1007/s11042-022-12668-8
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Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data International Journal of Data Science and Analytics 13(4), 335–362 (2022)
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