Paper Citation Record · LEDGER

Comparing BERT against traditional machine learning text classification

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2005.13012.

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

pith.paper-citation-record.v1
2005.13012 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:16:25.279603Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T14:06:27.358009Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation efa43881-7939-4c36-858a-249d2262a9d7 · inbound

Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness cites this paper.

Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness Comparing BERT against traditional machine learning text classification

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T21:16:25.279603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c31bd3c2-be97-4060-8b28-beb3c376f841 · inbound

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models cites this paper.

To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models Comparing BERT against traditional machine learning text classification

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T05:54:33.744951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ea8ee23-1e18-41d3-b507-23fb4c15b95b · inbound

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework cites this paper.

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework Comparing BERT against traditional machine learning text classification

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T23:04:09.398615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 387520b6-c0ff-420c-a816-24b2b7820324 · inbound

LLM Content Moderation and User Satisfaction: Evidence from Response Refusals in Chatbot Arena cites this paper.

LLM Content Moderation and User Satisfaction: Evidence from Response Refusals in Chatbot Arena Comparing BERT against traditional machine learning text classification

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:35.867410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d1693c7-dd13-4e80-8830-981c84560056 · inbound

An Improved Quantum Software Challenges Classification Approach using Transfer Learning and Explainable AI cites this paper.

An Improved Quantum Software Challenges Classification Approach using Transfer Learning and Explainable AI Comparing BERT against traditional machine learning text classification

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:06:27.360346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bd2fc01a-bd2b-41db-b2ef-e940cc20bc15 · inbound

Measuring and Evaluating the Performance of Generative AI Models for Scam Detection cites this paper.

Measuring and Evaluating the Performance of Generative AI Models for Scam Detection Comparing BERT against traditional machine learning text classification

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T18:19:26.407799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.