Paper Citation Record · LEDGER

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels

As of 13 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 2 inbound Pith citation observations for arXiv:2507.01077.

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

pith.paper-citation-record.v1
2507.01077 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:13:13.716554Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T10:00:03.036921Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T10:04:06.557061Z

Reference resolution

15 of 15 outbound references displayed

verified exact2
verified fuzzy1
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 523306a2-c862-4def-b72f-3646d95ee00d · outbound

This paper cites Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.172479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1959b81-b6a1-4f0b-b720-e227e7aaedcd · outbound

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

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.207839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1aac4a0-98ef-4c01-9cd6-217d7b40f60f · outbound

This paper cites LogBERT: Log Anomaly Detection via BERT.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels LogBERT: Log Anomaly Detection via BERT

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.244173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fbbb301-8c46-4ff4-a6e0-9b05a2125e8b · outbound

This paper cites LAnoBERT: System Log Anomaly Detection based on BERT Masked Language Model.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels LAnoBERT: System Log Anomaly Detection based on BERT Masked Language Model

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.279632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 022175cd-f616-4afb-adb4-f4dde59c550b · outbound

This paper cites CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.312978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf71a24e-9cc6-43e0-b2ef-095fc467dcdf · outbound

This paper cites Weakly Supervised Anomaly Detection via Knowledge-Data Alignment.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Weakly Supervised Anomaly Detection via Knowledge-Data Alignment

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:13:14.023231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3747d2fa-2e02-482f-92ce-2f543d9c03e5 · outbound

This paper cites Few-shot Anomaly Detection in Text with Deviation Learning.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Few-shot Anomaly Detection in Text with Deviation Learning

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:13:13.935557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4598807b-5fd5-4a9d-9bae-86193c0fc093 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Neural Machine Translation of Rare Words with Subword Units

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.419351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76957530-5d5b-4134-8f96-4bc909424250 · outbound

This paper cites Language models are unsupervised multitask learners,.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Language models are unsupervised multitask learners,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:13:14.188552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9e9cf39e-a9d6-473d-b721-7d3b5a6a9659 · outbound

This paper cites Qwen2 Technical Report.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Qwen2 Technical Report

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.491057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27da92e4-c0e4-4398-a598-72fbff91106f · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Lora: Low-rank adaptation of large language models,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.609435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd394821-23b0-4cb4-8f07-a091a3da9bc3 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.681792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24b6a02a-c74a-4234-8b28-f6a87754ea52 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Training Compute-Optimal Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.716554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f982b595-b7b5-41da-be7c-47a2d8f9f30f · outbound

This paper cites Don't Stop Pretraining: Adapt Language Models to Domains and Tasks.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels Don't Stop Pretraining: Adapt Language Models to Domains and Tasks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.562397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a3e35f7-6ea2-41da-b62c-2ae3130d0ab1 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels LoRA: Low-Rank Adaptation of Large Language Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:13.645996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation bc786e7e-de04-4881-81b1-74cfd1bf4b70 · inbound

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis cites this paper.

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:25:19.068095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e5f66613-8484-47fd-918b-bc8b16acef50 · inbound

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis cites this paper.

LLM4Log: A Systematic Review of Large Language Model-based Log Analysis Good Enough to Learn: LLM-based Anomaly Detection in ECU Logs without Reliable Labels

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-21T10:04:06.558724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.