Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T21:44:03.982650Z
Paper Citation Record · LEDGER
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models
As of 8 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2502.09385.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
12 of 12 outbound references displayed
- verified exact0
- verified fuzzy10
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 2775465d-1985-4e8f-9bfa-a89d6290ec91 · outbound
This paper cites Strategically-motivated advanced persistent threat: Definition, process, tactics and a disinformation model of coun- terattack,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Strategically-motivated advanced persistent threat: Definition, process, tactics and a disinformation model of coun- terattack,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.091945Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 65873729-e507-4f93-8bec-5a3ebde0fd45 · outbound
This paper cites A systematic literature review on advanced persistent threat behaviors and its detection strategy,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A systematic literature review on advanced persistent threat behaviors and its detection strategy,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.083545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation aa2e16b2-0c4e-4fbe-9a2d-d07db58ac8b9 · outbound
This paper cites A survey on evaluation of large language models,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A survey on evaluation of large language models,
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:44:03.953133Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 345d1aec-2a6f-40e2-8300-4858a48b9913 · outbound
This paper cites Large Language Models in Cybersecurity: State-of-the-Art.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Large Language Models in Cybersecurity: State-of-the-Art
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T21:44:03.956555Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 675ee37c-4e7c-4cc4-ba22-e11100616c44 · outbound
This paper cites A scalable and efficient outlier detection strategy for categorical data,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A scalable and efficient outlier detection strategy for categorical data,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.070578Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 57e2fb60-1b44-4a22-bcd5-d13cfe67b89b · outbound
This paper cites The odd one out: Identifying and char- acterising anomalies,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models The odd one out: Identifying and char- acterising anomalies,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.063610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c33c07af-37b3-4a0f-acd0-27f989d3cc11 · outbound
This paper cites Outlier detection for transaction databases using association rules,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Outlier detection for transaction databases using association rules,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.057036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2de9c4e7-b15f-41ed-82c3-98c7c9148a2d · outbound
This paper cites A baseline for unsupervised advanced persistent threat detection in system-level provenance,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A baseline for unsupervised advanced persistent threat detection in system-level provenance,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.049652Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6befc9b3-7b9e-4715-83fb-ef03d2be19dd · outbound
This paper cites A rule mining-based advanced persistent threats detection system,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A rule mining-based advanced persistent threats detection system,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.040118Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 20d2946e-9b08-40e9-9a1e-ab90f4e57bfd · outbound
This paper cites Hack me if you can: Aggregating autoencoders for countering persistent access threats within highly imbalanced data,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Hack me if you can: Aggregating autoencoders for countering persistent access threats within highly imbalanced data,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.031930Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 30b4e05e-6547-4488-905c-a72349ac2581 · outbound
This paper cites A survey of large language models for cyber threat detection,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A survey of large language models for cyber threat detection,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.022110Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d1ab48f8-65a2-4175-9fec-8f21b8b85e47 · outbound
This paper cites Cysecbert: A domain-adapted language model for the cybersecurity domain,.
APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Cysecbert: A domain-adapted language model for the cybersecurity domain,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T21:44:04.011803Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Pith citing papers
No inbound Pith citation observations are available.