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Paper Citation Record · LEDGER

How to Fine-Tune BERT for Text Classification?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:1905.05583.

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

pith.paper-citation-record.v1
1905.05583 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 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 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:46:03.507296Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
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External citation measurements

95
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5041efed-ce41-4506-8160-4923527fe180 · inbound

To Tune or Not To Tune? How About the Best of Both Worlds? cites this paper.

To Tune or Not To Tune? How About the Best of Both Worlds? How to Fine-Tune BERT for Text Classification?

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-25T00:46:30.640759Z

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=2026-05-25T00:45:10.865484Z digest=sha256:1897babe25d65c67269c639199c562d4031c124425304eb90381a48c5c78ac0d

Observation 891a41cc-66a5-4ea0-bff3-4a3073492f16 · inbound

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

FinBERT: Financial Sentiment Analysis with Pre-trained Language Models How to Fine-Tune BERT for Text Classification?

Reference 29

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verified exact
arxiv_id, observed 2026-05-15T20:26:05.125770Z

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=2026-05-15T20:26:04.766701Z digest=sha256:77710805787b6777d0bc4a11020bb097274a348d254a381ab4b25aa7a147f1ea

Observation e4e5b810-f296-40b7-be6f-a77e1dd6a4c6 · inbound

OPT: Open Pre-trained Transformer Language Models cites this paper.

OPT: Open Pre-trained Transformer Language Models How to Fine-Tune BERT for Text Classification?

Reference 78

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metadata mismatch
arxiv_id, observed 2026-05-10T20:53:17.383063Z

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=arxiv_source observed=2026-05-10T20:53:16.720145Z digest=sha256:77118707fc8c52107494ab26012ce7a389910d2ea45fdd9278ba32984d48d59f

Observation 50a35f0b-5963-43f7-9d04-a9077cb23b78 · inbound

Towards the Anonymization of the Language Modeling cites this paper.

Towards the Anonymization of the Language Modeling How to Fine-Tune BERT for Text Classification?

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-23T06:32:39.544581Z

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=2026-05-23T06:28:16.975305Z digest=sha256:a7abbbd5e4d04db9c5eb9cc2dd2c395e8b9d6715a7cd6f99beba9f945302e49f

Observation 6fb85b13-196f-4e51-aaf3-a5a4ed227fc5 · inbound

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

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

Resolution
unresolved
no resolver link, observed 2026-08-09T10:46:03.507296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:46:03.507296Z digest=sha256:c0caa2b0e933d4bd39ace8268dea2606ad385a6e160edd6b46995e953efca820

Observation 8945b60d-bc60-41cf-855e-d76e45f9745d · inbound

Stay Focused: Problem Drift in Multi-Agent Debate cites this paper.

Stay Focused: Problem Drift in Multi-Agent Debate How to Fine-Tune BERT for Text Classification?

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T01:52:22.981793Z

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=2026-05-23T01:48:50.818281Z digest=sha256:bf00738f40156312509945af4c6d1664b35337d5747bf0efdda9d153760af6cf

Observation ec4d545e-f24f-47f3-9818-38e7563cb046 · inbound

Optimising Language Models for Downstream Tasks: A Post-Training Perspective cites this paper.

Optimising Language Models for Downstream Tasks: A Post-Training Perspective How to Fine-Tune BERT for Text Classification?

Reference 214

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:44.568882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:44.568882Z digest=sha256:753aed2de9755dac1571fb3d5fe08a6d3fa8d8bda6771f8a032b4b8ca5fc8290

Observation 9bd6e89e-2d7d-44c6-9d8e-4c57d51c1a67 · inbound

Leveraging Machine Learning and Enhanced Parallelism Detection for BPMN Model Generation from Text cites this paper.

Leveraging Machine Learning and Enhanced Parallelism Detection for BPMN Model Generation from Text How to Fine-Tune BERT for Text Classification?

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T18:27:20.374992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:27:20.374992Z digest=sha256:34c9652b5a14e9e08c42ca953c82179e0251bcc55a2ae59798104a800752b13c

Observation d63fe4c4-efae-4003-a284-2e58a6e4d6a0 · inbound

Tiny Reward Models cites this paper.

Tiny Reward Models How to Fine-Tune BERT for Text Classification?

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T17:48:07.198467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:48:07.198467Z digest=sha256:4ad894f9f5b67033e70aa7ea27f15d8e6210973a8227a5fb606e85afe98f714f

Observation 599e3490-855f-4404-9a87-a9e8ea1f551f · inbound

Political Leaning and Politicalness Classification of Texts cites this paper.

Political Leaning and Politicalness Classification of Texts How to Fine-Tune BERT for Text Classification?

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T16:21:11.080273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:21:11.080273Z digest=sha256:5f740f2a46595f4681179e58f91ffc5e5a81dfdf06dae549e6779fe87dd0402f

Observation 650c6b4b-4793-4eda-9bfa-6a10180ea15e · inbound

Optimizing Small Transformer-Based Language Models for Multi-Label Sentiment Analysis in Short Texts cites this paper.

Optimizing Small Transformer-Based Language Models for Multi-Label Sentiment Analysis in Short Texts How to Fine-Tune BERT for Text Classification?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T05:46:09.690338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:46:09.690338Z digest=sha256:a4b4d0cd0d7e7a8dac845bb90d11e86e856b1f61d91bfafc3c76d24ff9581cdc

Observation c3165a80-ad5d-4682-9f1b-3a18f733598d · inbound

ADMEDTAGGER: an annotation framework for distillation of expert knowledge for the Polish medical language cites this paper.

ADMEDTAGGER: an annotation framework for distillation of expert knowledge for the Polish medical language How to Fine-Tune BERT for Text Classification?

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-21T15:54:14.530955Z

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=2026-05-21T15:53:11.348103Z digest=sha256:a1230d649d16a6839f5f78bc884b2899e3d7478588236026c6a2947469997b1c

Observation aede7dd5-0a44-48ae-9e09-71d11c5b2dac · inbound

Enhancing Construction Worker Safety in Extreme Heat: A Machine Learning Approach Utilizing Wearable Technology for Predictive Health Analytics cites this paper.

Enhancing Construction Worker Safety in Extreme Heat: A Machine Learning Approach Utilizing Wearable Technology for Predictive Health Analytics How to Fine-Tune BERT for Text Classification?

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:51:04.336365Z

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=2026-05-10T02:44:28.708504Z digest=sha256:2061c6d83e03b0df3e38824f195cd09cd38d0f8a52a853eea5bd7162347cafea

Observation 0b9ff41b-d278-418b-926a-365583541908 · inbound

Exploring Data Augmentation and Resampling Strategies for Transformer-Based Models to Address Class Imbalance in AI Scoring of Scientific Explanations in NGSS Classroom cites this paper.

Exploring Data Augmentation and Resampling Strategies for Transformer-Based Models to Address Class Imbalance in AI Scoring of Scientific Explanations in NGSS Classroom How to Fine-Tune BERT for Text Classification?

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:39:50.430827Z

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=2026-05-15T07:36:07.321806Z digest=sha256:9c8147eae297c71bc94f5c5cfb49d8b2454f16fd68c3eb0d3b9892d8dc619199

Observation cf110b5f-cb51-49f3-b8fe-c6051ee61527 · inbound

Response-free item difficulty modelling for multiple-choice items with fine-tuned transformers: Component-wise representation and multi-task learning cites this paper.

Response-free item difficulty modelling for multiple-choice items with fine-tuned transformers: Component-wise representation and multi-task learning How to Fine-Tune BERT for Text Classification?

Reference 170

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:23:12.844150Z

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=arxiv_source observed=2026-05-19T20:22:55.750693Z digest=sha256:33dbee3835eec009cc09dceb81723d2e29c62aea2ba678b3e4fb32870d85380e

Observation 242d29d0-cac7-45bb-a536-58d5d3555d9a · inbound

PortBERT: Navigating the Depths of Portuguese Language Models cites this paper.

PortBERT: Navigating the Depths of Portuguese Language Models How to Fine-Tune BERT for Text Classification?

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T23:06:20.124854Z

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=arxiv_source observed=2026-06-28T14:43:28.401687Z digest=sha256:bdfce61dd0cb4f1abf59c65353640801c8c4e4c56e8920f2696511517c08846b