Paper Citation Record · LEDGER

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum

As of 15 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2509.00069.

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

pith.paper-citation-record.v1
2509.00069 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:06:48.884545Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:34:16.651254Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

verified exact1
verified fuzzy12
unresolved10
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bbca2f09-099f-4024-adf6-c07d0177e43f · outbound

This paper cites an unresolved cited work.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:06:49.161078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dbeb5326-f914-457b-b7f3-3d5292a4be6d · outbound

This paper cites These visual explanations are seamlessly integrated into the user interface to enhance interpretability.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum These visual explanations are seamlessly integrated into the user interface to enhance interpretability

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.153619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d009f57b-d329-44a4-a31a-6cfa0e3ac6ed · outbound

This paper cites This improves usability, reduces manual effort, and encourages a wider adoption of LLMs in cybersecurity workflows.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum This improves usability, reduces manual effort, and encourages a wider adoption of LLMs in cybersecurity workflows

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.145078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4d115e5d-28ee-4179-a0b2-ad638e998049 · outbound

This paper cites RoBERTa was ulti- mately selected as the optimal choice due to its high accuracy and practical performance.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum RoBERTa was ulti- mately selected as the optimal choice due to its high accuracy and practical performance

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.137164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bd9571ed-b348-4d8b-b004-a3b4730a92f8 · outbound

This paper cites black -box.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum black -box

Reference 5

Resolution: malformed identifier; raw_fallback, observed 2026-08-05T16:06:49.128273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1dc980bb-3f4d-4052-ab0f-dc1f83c24de1 · outbound

This paper cites Log File Analysis Based on Machine Learning: A Survey: Survey.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Log File Analysis Based on Machine Learning: A Survey: Survey

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.119158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 80df61b0-8b25-4aa2-90fb-1dbdff8d87ae · outbound

This paper cites HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs).

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.827171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc4eabd4-105b-4834-9bb8-860cb6fe61b5 · outbound

This paper cites The Falcon Series of Open Language Models.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum The Falcon Series of Open Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.830525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e887b2b3-9a7c-4891-9a4c-ad74e3111d1d · outbound

This paper cites Cygent: A cybersecurity conversational agent with log summarization powered by gpt-3.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Cygent: A cybersecurity conversational agent with log summarization powered by gpt-3

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.110508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2c7f85fc-f935-4364-addb-68ab211073c2 · outbound

This paper cites Transformer-based llms in cybersecurity: An in-depth study on log anomaly detection and conversational defense mechanisms.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Transformer-based llms in cybersecurity: An in-depth study on log anomaly detection and conversational defense mechanisms

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.102182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 278b0f8f-480d-4120-a663-f3de6f36115d · outbound

This paper cites What Does BERT Look At? An Analysis of BERT's Attention.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum What Does BERT Look At? An Analysis of BERT's Attention

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.840611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 236c54df-afe9-4c27-9812-813a3bc5b5f9 · outbound

This paper cites 2023 Cybersecurity Almanac: 100 Facts, Figures, Predictions, And Statistics.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum 2023 Cybersecurity Almanac: 100 Facts, Figures, Predictions, And Statistics

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.093085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 998caebc-2a46-441e-9f90-81678dbf9995 · outbound

This paper cites Machine learning based anomaly detection of log files using ensemble learning and self -attention.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Machine learning based anomaly detection of log files using ensemble learning and self -attention

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.848909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fb45a40-9655-41d0-9a78-107421a6d7d0 · outbound

This paper cites LLMeLog: An Approach for Anomaly Detection based on LLM-enriched Log Events.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum LLMeLog: An Approach for Anomaly Detection based on LLM-enriched Log Events

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.084582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0bd9258e-dabc-4189-a7c9-4202b94577c5 · outbound

This paper cites DeBERTa: Decoding-enhanced BERT with Disentangled Attention.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum DeBERTa: Decoding-enhanced BERT with Disentangled Attention

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.854403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab252a9a-7cf1-4b8f-a554-b7b0f9bc8ce6 · outbound

This paper cites Captum: A unified and generic model interpretability library for PyTorch.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Captum: A unified and generic model interpretability library for PyTorch

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.857320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41605253-0bbc-4dd9-ab99-32c6721d7699 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.860690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80ab0a17-4cab-46de-acf4-b8a8d1984148 · outbound

This paper cites Framework for Improving Critical Infrastructure Cybersecurity, Version 1.1.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Framework for Improving Critical Infrastructure Cybersecurity, Version 1.1

Reference 18

Resolution: malformed identifier; raw_fallback, observed 2026-08-05T16:06:49.073705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a8699a9d-f857-4b2f-8e58-5a4270233d16 · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum YaRN: Efficient Context Window Extension of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.866757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50f26e74-e8eb-4e81-8cfa-59043f9b667d · outbound

This paper cites Explainable AI for cybersecurity automation, intelli - gence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Explainable AI for cybersecurity automation, intelli - gence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.065352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2d9430ad-4525-4099-9f9e-9792f0c24f2c · outbound

This paper cites IoT Dynamic Log File Analysis: Security Approach f or Anomaly Detection In Multi Sensor Environment.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum IoT Dynamic Log File Analysis: Security Approach f or Anomaly Detection In Multi Sensor Environment

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.056462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ce54a53-b00b-421d-8694-2882647e10d8 · outbound

This paper cites A survey on forensic investigation of operating system logs.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum A survey on forensic investigation of operating system logs

Reference 22

Resolution: verified exact; doi, observed 2026-08-05T16:06:48.917774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7140b10e-8efd-413e-8d95-812bd42aa285 · outbound

This paper cites Cldtlog: system log anomaly detection method based on contrastive learning and dual objective tasks.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Cldtlog: system log anomaly detection method based on contrastive learning and dual objective tasks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T16:06:48.878901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18ce8461-bce3-4130-adb7-10794d0cc960 · outbound

This paper cites BertViz: A tool for visualizing multihead self -attention in the BERT model.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum BertViz: A tool for visualizing multihead self -attention in the BERT model

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.046937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 96f80dda-f348-4ff7-b5a8-432327daa619 · outbound

This paper cites Loghub: A large collection of system log datasets for ai-driven log analytics.

AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Loghub: A large collection of system log datasets for ai-driven log analytics

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:06:49.038586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 3c4730da-1b34-4f90-bee9-b750bb43d336 · inbound

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations cites this paper.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T00:34:16.651254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.