Paper Citation Record · LEDGER

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study

As of 22 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2412.00098.

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

pith.paper-citation-record.v1
2412.00098 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:05:09.727538Z

measured 35 of 35 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:08:35.063126Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T15:08:35.695109Z

Reference resolution

34 of 34 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3d275193-437c-4ddd-aef2-af9e566450ae · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Exploring small language models with prompt-learning paradigm for efficient domain-specific text classifica- tion,

Reference 1

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Observation df91749f-5bcc-4d3a-ba63-c8cd92dcb0e2 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Multilabel text classification with label-dependent representation,

Reference 2

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Observation c61a2f72-416a-4bea-a6eb-3858a6c6f172 · outbound

This paper cites Survey of fake news datasets and detection methods in european and asian languages,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Survey of fake news datasets and detection methods in european and asian languages,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:10.278350Z

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Observation e2e1f70e-94a0-48ac-a718-ecbc929d21a7 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Novel deep learning approach for sci- entific literature classification,

Reference 4

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Observation be024fcf-4d84-44a3-b4c9-c6b0197d104f · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Benchmarking for biomedical natural language processing tasks with a domain specific albert,

Reference 5

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Observation d7dbaa7a-ae6f-460c-8e5a-c0c807254c9f · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study A brief survey of text classification methods,

Reference 6

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Observation 3979f0ed-3332-4bf8-ad6e-c56b19e11959 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study A survey of text classification with transformers: How wide? how large? how long? how accurate? how expensive? how safe?,

Reference 7

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Observation 6f02f901-cf37-4d73-b8d5-973e6be8a35b · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Survey of pre-trained models for natural language processing,

Reference 8

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Observation 20d3566e-b6dd-4d5e-a74a-18e020809d63 · outbound

This paper cites Text Classification via Large Language Models.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Text Classification via Large Language Models

Reference 9

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Observation fcefec19-ae0a-4d83-a7af-ac5b5247b2d0 · outbound

This paper cites A Survey of Large Language Models.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study A Survey of Large Language Models

Reference 10

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Observation 0f238e51-9663-4a82-aa52-11fb80b52252 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Cross-domain limi- tations of neural models on biomedical relation classification,

Reference 11

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Observation 95a3f5e1-d847-41ca-bf31-3053257b34de · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study FinBERT: Financial Sentiment Analysis with Pre-trained Language Models

Reference 12

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Observation cbf1dcfb-4c6a-4c05-96c8-650b3bf1673d · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Sentiment analysis with neural models for hungarian,

Reference 13

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Observation 3d734dde-7da8-47b1-9695-a4217c5ec1b5 · outbound

This paper cites Topic modeling: a comprehensive review,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Topic modeling: a comprehensive review,

Reference 14

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Observation f6ca4350-5b15-4ae4-ad76-830050a38e33 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Inte- grating text classification into topic discovery using semantic embedding models,

Reference 15

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Observation 372af3c6-16f7-4dce-8e49-185a282aa21c · outbound

This paper cites Attention is all you need,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Attention is all you need,

Reference 16

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Observation 2160887a-35bb-44ab-a34f-a4b59b8c3d3a · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 17

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Observation e3b6b8ed-e982-477d-947a-886665bf6c01 · outbound

This paper cites Language model behavior: A compre- hensive survey,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Language model behavior: A compre- hensive survey,

Reference 18

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Observation 5d020339-7d97-46f2-af4e-4e734122e62c · outbound

This paper cites Large language models for text classification: From zero-shot learning to fine-tuning,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Large language models for text classification: From zero-shot learning to fine-tuning,

Reference 19

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Observation 5caf9eef-3df4-4708-8200-9878a773aadf · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study SciBERT: A Pretrained Language Model for Scientific Text

Reference 20

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Observation e906403f-ca39-41ec-8eef-63cd274415e1 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Biobert: a pre-trained biomedical language representation model for biomedical text mining,

Reference 21

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Observation 395bf832-112c-48a7-8d6c-d7d1bbff2e3a · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Transfer learning in biomedical natural lan- guage processing: An evaluation of bert and elmo on ten benchmarking datasets,

Reference 22

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Observation 74c0359f-88ab-498c-bc10-7fae40335045 · outbound

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Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Finbert: A pre-trained financial language representation model for financial text mining,

Reference 23

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Observation 5a8a1cfb-848b-400c-9259-6e523e322bb4 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Structured information extraction from complex scientific text with fine-tuned large language models

Reference 24

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Observation 6ecf88dc-ef12-4507-9159-a122f9525817 · outbound

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Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Matscibert: A materials domain language model for text mining and information extraction,

Reference 25

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Medibiodeberta: Biomedical lan- guage model with continuous learning and intermediate fine-tuning,

Reference 26

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Observation 2f166ef7-5381-441a-8a3b-56a2be656979 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Hdltex: Hierarchical deep learning for text classification,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:10.039692Z

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Observation d4370668-9b80-4404-bf2f-bfd330789383 · outbound

This paper cites A lightweight biomedical named entity recognition with pre-trained model,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study A lightweight biomedical named entity recognition with pre-trained model,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:10.021078Z

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Observation 5fc5fd26-79b8-4410-94ff-4a94a0338ed1 · outbound

This paper cites Named entity recognition using transfer learning with the fusion of pre-trained scibert language model and bi-directional long short term memory,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Named entity recognition using transfer learning with the fusion of pre-trained scibert language model and bi-directional long short term memory,

Reference 29

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Observation 43b1a068-7ab6-4c08-9cb7-5bd140ccf446 · outbound

This paper cites A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers

Reference 30

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Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study S2ORC: The Semantic Scholar Open Research Corpus

Reference 31

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study A Survey of Active Learning for Text Classification using Deep Neural Networks

Reference 32

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This paper cites Recurrent convolutional neural networks for text classification,.

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Recurrent convolutional neural networks for text classification,

Reference 33

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Observation a9cc635d-3785-41ff-a52e-b7a7f272ebc4 · outbound

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

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks

Reference 34

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Pith citing papers

Observation 1e2252b3-196f-4137-81d9-6098adbcdcc1 · inbound

Efficient Scientific Full Text Classification: The Case of EICAT Impact Assessments cites this paper.

Efficient Scientific Full Text Classification: The Case of EICAT Impact Assessments Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study

Reference 31

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Source-reported events for the cited work

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