Paper Citation Record · LEDGER

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting

As of 17 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2504.19021.

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

pith.paper-citation-record.v1
2504.19021 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:07:10.158306Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

33 of 33 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b4ebb0e5-23cd-4b74-a7cb-7a7a0f402cfb · outbound

This paper cites A survey of text classification with transformers: How wide? how large? how long? how accurate? how expensive? how safe?,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting A survey of text classification with transformers: How wide? how large? how long? how accurate? how expensive? how safe?,

Reference 1

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Observation fe63895d-e16f-4872-98a4-c6ec802e21f0 · outbound

This paper cites Improving imbalanced scientific text classification using sampling strategies and dictionaries,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Improving imbalanced scientific text classification using sampling strategies and dictionaries,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:07:10.655153Z

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Observation f69ebaf9-9648-40e2-a8e2-ff12759ff8df · outbound

This paper cites Exploring small language models with prompt-learning paradigm for efficient domain-specific text classifica- tion,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Exploring small language models with prompt-learning paradigm for efficient domain-specific text classifica- tion,

Reference 3

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Observation ab448e4d-feb1-44e4-82c8-173e64c228cf · outbound

This paper cites Multilabel text classification with label-dependent representation,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Multilabel text classification with label-dependent representation,

Reference 4

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Observation 76fc3f7b-4014-4561-85e5-bc7909c3f5c2 · outbound

This paper cites Novel deep learning approach for sci- entific literature classification,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Novel deep learning approach for sci- entific literature classification,

Reference 5

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Observation cde463a4-d8c1-4973-84dd-ae5e27e1a12d · outbound

This paper cites Benchmarking for biomedical natural language processing tasks with a domain specific albert,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Benchmarking for biomedical natural language processing tasks with a domain specific albert,

Reference 6

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Observation 4c9559b4-d992-4ba3-a781-14e47bc61175 · outbound

This paper cites A brief survey of text classification methods,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting A brief survey of text classification methods,

Reference 7

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Observation 7318ed90-3843-4be9-882c-b9d7e78e2b49 · outbound

This paper cites Deep learning–based text classification: a comprehensive review,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Deep learning–based text classification: a comprehensive review,

Reference 8

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Observation 51f22e61-079f-4db3-9478-3fbdae5d56db · outbound

This paper cites Survey of pre-trained models for natural language processing,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Survey of pre-trained models for natural language processing,

Reference 9

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Observation 2330883f-1375-431b-ad48-c91e30597435 · outbound

This paper cites Text Classification via Large Language Models.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Text Classification via Large Language Models

Reference 10

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Observation 99cdc651-2efe-4bbc-a588-c6cb57b357ac · outbound

This paper cites Cross-domain limi- tations of neural models on biomedical relation classification,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Cross-domain limi- tations of neural models on biomedical relation classification,

Reference 11

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Observation edc6b0bb-3e77-4378-8f73-d817008216b3 · outbound

This paper cites FinBERT: Financial Sentiment Analysis with Pre-trained Language Models.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting FinBERT: Financial Sentiment Analysis with Pre-trained Language Models

Reference 12

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Observation 80899e52-1c61-46e3-9d16-3d60e99f7b72 · outbound

This paper cites Sentiment analysis with neural models for hungarian,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Sentiment analysis with neural models for hungarian,

Reference 13

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Observation e2e95a54-acd6-4dde-81fd-41edb0f1aa88 · outbound

This paper cites Topic modeling: a comprehensive review,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Topic modeling: a comprehensive review,

Reference 14

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Observation 71bf5e89-56b6-458c-8622-63d6ae13eae7 · outbound

This paper cites Inte- grating text classification into topic discovery using semantic embedding models,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Inte- grating text classification into topic discovery using semantic embedding models,

Reference 15

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Observation 901abf8b-72bb-44f7-9708-ed00781a5ea6 · outbound

This paper cites A Survey of Large Language Models.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting A Survey of Large Language Models

Reference 16

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Observation 3d714535-bbb1-4ad2-a629-4b57bd6d1927 · outbound

This paper cites Attention is all you need,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Attention is all you need,

Reference 17

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Observation e63ce8fc-9cae-4d27-967c-41af186cd381 · outbound

This paper cites SciBERT: A Pretrained Language Model for Scientific Text.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting SciBERT: A Pretrained Language Model for Scientific Text

Reference 18

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Observation 3ab300e7-7ba1-427f-8392-a6d0d322a2a8 · outbound

This paper cites Biobert: a pre-trained biomedical language representation model for biomedical text mining,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Biobert: a pre-trained biomedical language representation model for biomedical text mining,

Reference 19

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Observation 183cede3-664d-4562-ac6a-7ab26d591413 · outbound

This paper cites Fine-tuning large language models for scientific text classification: A comparative study,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Fine-tuning large language models for scientific text classification: A comparative study,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:07:10.529644Z

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Observation 525213a1-78c7-4caa-9973-d884ca4daf77 · outbound

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

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 21

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Observation 83296ff9-8d8e-4bba-810c-e31dbc25dad9 · outbound

This paper cites Finbert: A pre-trained financial language representation model for financial text mining,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Finbert: A pre-trained financial language representation model for financial text mining,

Reference 22

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Observation d523cf3f-53b3-4bc1-a8ed-c95d1d4b5ef8 · outbound

This paper cites Structured information extraction from complex scientific text with fine-tuned large language models.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Structured information extraction from complex scientific text with fine-tuned large language models

Reference 23

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Observation 8bd3f5ee-978f-45e2-b59c-bfffa581718f · outbound

This paper cites Matscibert: A materials domain language model for text mining and information extraction,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Matscibert: A materials domain language model for text mining and information extraction,

Reference 24

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Observation e689b611-87b6-4d3f-bc9c-c3cbbfa18c04 · outbound

This paper cites Transfer learning in biomedical natural lan- guage processing: An evaluation of bert and elmo on ten benchmarking datasets,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Transfer learning in biomedical natural lan- guage processing: An evaluation of bert and elmo on ten benchmarking datasets,

Reference 25

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Observation 32942ef8-ec6c-4ad0-8a9f-dcdc3dc2697f · outbound

This paper cites Medibiodeberta: Biomedical lan- guage model with continuous learning and intermediate fine-tuning,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Medibiodeberta: Biomedical lan- guage model with continuous learning and intermediate fine-tuning,

Reference 26

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Observation dbced679-6cbb-4e91-8808-3868c8ef2628 · outbound

This paper cites The classification of short scientific texts using pretrained bert model,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting The classification of short scientific texts using pretrained bert model,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:07:10.470233Z

Source-reported events for the cited work

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Observation b1733f7b-7c13-4381-998d-14aaaaca70d9 · outbound

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Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Ensemble learning with pre-trained transformers for crash severity classification: A deep nlp approach,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:07:10.456697Z

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Observation 5ce674ab-26e8-468a-98ae-4315901872f9 · outbound

This paper cites EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks

Reference 29

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Observation 9646aec1-2c1b-4339-80b5-366c1804fc10 · outbound

This paper cites Hdltex: Hierarchical deep learning for text classification,.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Hdltex: Hierarchical deep learning for text classification,

Reference 30

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Observation 0bc84a92-9491-495d-a7f9-c1ff20108332 · outbound

This paper cites A Survey of Active Learning for Text Classification using Deep Neural Networks.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting A Survey of Active Learning for Text Classification using Deep Neural Networks

Reference 31

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Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Recurrent convolutional neural networks for text classification,

Reference 32

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This paper cites Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks.

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks

Reference 33

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