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Paper Citation Record · LEDGER

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2502.02893.

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

pith.paper-citation-record.v1
2502.02893 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:46:03.550554Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8148fe9b-8619-4380-b2f4-3cb3ff6bc06f · outbound

This paper cites The effect of word of mouth on sales: Online book reviews,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs The effect of word of mouth on sales: Online book reviews,

Reference 1

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Observation 4847d2a4-2e75-4e3b-a8d1-133048774d12 · outbound

This paper cites Word of mouth for movies: Its dynamics and impact on box office revenue,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Word of mouth for movies: Its dynamics and impact on box office revenue,

Reference 2

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Observation be28d2a2-6048-40c1-8311-341ea4214c1c · outbound

This paper cites Overcoming the j-shaped distribution of product reviews,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Overcoming the j-shaped distribution of product reviews,

Reference 3

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Observation 5c5a0685-99d4-400e-96be-47315dd8bc82 · outbound

This paper cites The digitization of word of mouth: Promise and chal- lenges of online feedback mechanisms,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs The digitization of word of mouth: Promise and chal- lenges of online feedback mechanisms,

Reference 4

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Observation 2ece1b1c-71bf-4c7b-816d-cc9a075808e3 · outbound

This paper cites Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets,

Reference 5

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Observation 7c086f41-db47-4e58-86b7-43f6051f3c76 · outbound

This paper cites An analysis of sentiment: Methods, applications, and challenges,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs An analysis of sentiment: Methods, applications, and challenges,

Reference 6

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Observation e068a183-5b06-4bab-9a80-c96121f327f9 · outbound

This paper cites Sentiment analysis: An overview from linguistics,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Sentiment analysis: An overview from linguistics,

Reference 7

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Source-reported events for the cited work

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Observation 7c58ace4-49ac-4e68-ac83-7cd6283217db · outbound

This paper cites Sentiment analysis: A survey on design framework, applications and future scopes,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Sentiment analysis: A survey on design framework, applications and future scopes,

Reference 8

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Source-reported events for the cited work

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Observation 0aede5a0-7a29-45bc-9d40-9124a62964ff · outbound

This paper cites Machine learning algorithms for labeling: Where and how they are used?.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Machine learning algorithms for labeling: Where and how they are used?

Reference 9

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Observation 126b78de-ccdf-40d3-8061-00368c094299 · outbound

This paper cites Cheap and fast— but is it good? evaluating non-expert annotations for natural language tasks,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Cheap and fast— but is it good? evaluating non-expert annotations for natural language tasks,

Reference 10

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Observation bad629db-b2da-42d2-8e78-99148e30893c · outbound

This paper cites A review on large language models: Architectures, applications, taxonomies, open issues and challenges,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs A review on large language models: Architectures, applications, taxonomies, open issues and challenges,

Reference 11

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This paper cites Research and implementation of high computational power for training and inference of convolutional neural networks,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Research and implementation of high computational power for training and inference of convolutional neural networks,

Reference 12

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Source-reported events for the cited work

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This paper cites Lexicon- based methods for sentiment analysis,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Lexicon- based methods for sentiment analysis,

Reference 13

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This paper cites Thumbs up?: sentiment classifi- cation using machine learning techniques,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Thumbs up?: sentiment classifi- cation using machine learning techniques,

Reference 14

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This paper cites Machine learning in automated text categorization,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Machine learning in automated text categorization,

Reference 15

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Observation 7e16778e-3488-467e-9547-2d263c6dfeee · outbound

This paper cites Convolutional neural networks for sentence classification,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Convolutional neural networks for sentence classification,

Reference 16

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Long short-term memory,

Reference 17

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 18

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Observation 120e88a2-0d25-4e62-ae68-b392f2acfb48 · outbound

This paper cites Deep learning for sentiment analysis: A survey,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Deep learning for sentiment analysis: A survey,

Reference 19

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs XLNet: Generalized Autoregressive Pretraining for Language Understanding

Reference 20

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Imagenet: A large-scale hierarchical image database,

Reference 21

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Language Models are Few-Shot Learners

Reference 22

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Energy and policy considerations for deep learning in NLP,

Reference 23

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Frugalgpt: How to use large language models while reducing cost and improving performance,

Reference 24

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Memory-efficient pipeline-parallel dnn training,

Reference 25

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 26

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs How to Fine-Tune BERT for Text Classification?

Reference 27

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping

Reference 28

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Revealing the Dark Secrets of BERT

Reference 29

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Amazon Reviews Dataset,

Reference 30

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Learning word vectors for sentiment analysis,

Reference 31

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Tripadvisor hotel review dataset,

Reference 32

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

Reference 33

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Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Making pre-trained language models better few-shot learners,

Reference 34

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Observation aacfab5e-8ad5-43d1-a224-8e3404b828b0 · outbound

This paper cites Exploiting cloze questions for few shot text classification and natural language inference,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Exploiting cloze questions for few shot text classification and natural language inference,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T10:46:03.882057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T10:46:03.545554Z digest=sha256:4ae134afd6cfeff78684cd96bbcde2bf89136d00eaf769073b93cbd152f61b44

Observation 98c7a9af-f198-461a-bc26-aeb8508f0999 · outbound

This paper cites Google colaboratory,.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Google colaboratory,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T10:46:03.864131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T10:46:03.550554Z digest=sha256:f46a3b16a4c0b03f1109ce758fdbb35b216dc6b7d4478884e84bc0ee53fcc993

Observation f67ff1a7-20cf-4127-8c99-6c665d2c6957 · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

Lowering the Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-09T10:46:03.491426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:46:03.491426Z digest=sha256:2bc26c0afa1930491e104c2d3682606f05cbee1f9b5907169cf007bb62acbbe2

Pith citing papers

No inbound Pith citation observations are available.