Paper Citation Record · LEDGER

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT

As of 23 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2501.00241.

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

pith.paper-citation-record.v1
2501.00241 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:59:49.992315Z

measured 14 of 14 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 2026-08-06T16:21:11.036880Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:21:11.526261Z

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy11
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b24add1a-716d-4481-b1f9-dfd1c1477de1 · outbound

This paper cites Rethinking learning rate tuning in the era of large language models,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Rethinking learning rate tuning in the era of large language models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.204256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 751f6b06-02b6-469d-bbd2-1afb759209ea · outbound

This paper cites Evaluating the effectiveness of fine-tuning large language model for domain-specific task,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Evaluating the effectiveness of fine-tuning large language model for domain-specific task,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.189972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8a9f0b16-a98a-4850-b170-52546867dd5c · outbound

This paper cites Fine-tuning Large Language Models for Domain-specific Machine Translation.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Fine-tuning Large Language Models for Domain-specific Machine Translation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:49.945383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dd59be3-b112-4146-ba82-fcc2e47ddb35 · outbound

This paper cites Fine-tune it like i’m five: Supporting medical domain experts in training ner models using cloud, llm, and auto fine-tuning,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Fine-tune it like i’m five: Supporting medical domain experts in training ner models using cloud, llm, and auto fine-tuning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.174673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d46ef631-a3e3-47de-978a-db8cb63c9b39 · outbound

This paper cites Fine tuning llms for low resource languages,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Fine tuning llms for low resource languages,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.159936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4f326a27-b17c-486f-a0cd-38a2986fb4be · outbound

This paper cites Achieving peak perfor- mance for large language models: A systematic review,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Achieving peak perfor- mance for large language models: A systematic review,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:59:49.960332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a8cc98f-83a1-435e-b758-9f5b9f01cb2f · outbound

This paper cites Fine-tuned understanding: Enhancing social bot detection with transformer-based classification,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Fine-tuned understanding: Enhancing social bot detection with transformer-based classification,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.135124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5198498b-08ed-4af7-8c9d-12dea60705ec · outbound

This paper cites Layoutllm: Layout instruction tuning with large language models for document un- derstanding,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Layoutllm: Layout instruction tuning with large language models for document un- derstanding,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.119834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2d8d1f10-21a3-4384-a0f8-81f25064f312 · outbound

This paper cites Cyberbullying detection in social networks: A comparison between machine learning and transfer learning approaches,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Cyberbullying detection in social networks: A comparison between machine learning and transfer learning approaches,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.103738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation aa3e68cf-af38-4ac2-ae8f-0c3a9345e6e6 · outbound

This paper cites Hate speech and target community detection in nastaliq urdu using transfer learning techniques,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Hate speech and target community detection in nastaliq urdu using transfer learning techniques,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.089686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b5005fde-c2ad-49f6-9025-8167ab773dc0 · outbound

This paper cites Depression classification from tweets using small deep transfer learning language models,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Depression classification from tweets using small deep transfer learning language models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.075663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fd27a4d2-771f-4fc8-8452-90c57afd3c08 · outbound

This paper cites Agi-p: A gender identification framework for authorship analysis using customized fine-tuning of multilingual language model,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Agi-p: A gender identification framework for authorship analysis using customized fine-tuning of multilingual language model,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.060857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8a84259b-485e-4de2-a83c-76fc38dce86f · outbound

This paper cites Performance analysis of federated learning algorithms for multilingual protest news detection using pre-trained distilbert and bert,.

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT Performance analysis of federated learning algorithms for multilingual protest news detection using pre-trained distilbert and bert,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:59:50.045420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation d470a0e4-9a12-483e-811e-ec0cf860df80 · inbound

Political Leaning and Politicalness Classification of Texts cites this paper.

Political Leaning and Politicalness Classification of Texts Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:21:11.529108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.