Paper Citation Record · LEDGER

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

As of 16 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 7 inbound Pith citation observations for arXiv:2411.10918.

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

pith.paper-citation-record.v1
2411.10918 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:14:49.304233Z

measured 65 of 65 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:40.473768Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:22:24.835271Z

Reference resolution

58 of 58 outbound references displayed

verified exact1
verified fuzzy39
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d40fad5f-5aa7-4396-bb81-5e959c506116 · outbound

This paper cites Cyber-physical systems (cps),.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Cyber-physical systems (cps),

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.679809Z

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 081f70db-bdb7-4e24-bd1f-64f037089a7b · outbound

This paper cites A survey on cyber– physical systems security,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection A survey on cyber– physical systems security,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.655157Z

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 eb7e8ecd-991e-4ff1-b38e-aac9a0a5fb31 · outbound

This paper cites {SA VIOR}: Securing autonomous vehicles with robust physical invariants,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection {SA VIOR}: Securing autonomous vehicles with robust physical invariants,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.634747Z

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 6e5ae247-d6cc-4bec-bff1-7b15fa85cc03 · outbound

This paper cites A survey of physics-based attack detection in cyber-physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection A survey of physics-based attack detection in cyber-physical systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.612229Z

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 bbe1035a-fdcb-44ca-851f-3a92b8d3643e · outbound

This paper cites A systematic framework to generate invariants for anomaly detection in industrial control systems.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection A systematic framework to generate invariants for anomaly detection in industrial control systems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.586062Z

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 d23878d2-1431-44c5-8ae1-20662d987793 · outbound

This paper cites A review of anomaly detection strategies to detect threats to cyber-physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection A review of anomaly detection strategies to detect threats to cyber-physical systems,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.565037Z

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 8ca36f02-66bf-485a-8dce-cfaf2e6f53f4 · outbound

This paper cites Implementation of programmable{CPS}testbed for anomaly detection,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Implementation of programmable{CPS}testbed for anomaly detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.540726Z

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 9412c023-1c56-4255-92b4-3a8cd4dd1ffc · outbound

This paper cites Process safety management osha 3132,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Process safety management osha 3132,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.517868Z

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 2370d8d9-27fe-48f6-921f-466a2129fbe2 · outbound

This paper cites Nist special publication 800-82, revision 2: Guide to industrial control systems (ics) security,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Nist special publication 800-82, revision 2: Guide to industrial control systems (ics) security,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.487583Z

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 71a4eb2a-8263-4500-8ee5-36310f25ca43 · outbound

This paper cites What is the best way to document the control system?.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection What is the best way to document the control system?

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.468822Z

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 70954409-e565-42b6-ba7e-d6e8bdadf90e · outbound

This paper cites Swat: A water treatment testbed for research and training on ics security,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Swat: A water treatment testbed for research and training on ics security,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.044217Z

Source-reported events for the cited work

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Observation cbabb81a-5e26-42f1-b728-3bf00d25b226 · outbound

This paper cites Unified invariants for cyber-physical switched system stability,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Unified invariants for cyber-physical switched system stability,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.049207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bea8ed28-b967-4920-a625-6e2ad028b470 · outbound

This paper cites Artinali: dynamic invariant detection for cyber-physical system secu- rity,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Artinali: dynamic invariant detection for cyber-physical system secu- rity,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.422667Z

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 9f03e46e-513f-455d-aaf8-42e49e56a19c · outbound

This paper cites Hybrid statistical-machine learning for real-time anomaly detection in industrial cyber–physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Hybrid statistical-machine learning for real-time anomaly detection in industrial cyber–physical systems,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.397986Z

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 ad461226-53b8-464c-b6ba-39f79807a0a3 · outbound

This paper cites {SAIN}: Improving{ICS}attack detection sensitivity via{State-Aware}invariants,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection {SAIN}: Improving{ICS}attack detection sensitivity via{State-Aware}invariants,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.371707Z

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 1076b939-15b2-4fa2-ba0a-dc4345f4d054 · outbound

This paper cites Are language models actually useful for time series forecasting?.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Are language models actually useful for time series forecasting?

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.070233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e10f8822-89e2-4033-ae7a-377de22685e2 · outbound

This paper cites Uncovering Limitations of Large Language Models in Information Seeking from Tables.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Uncovering Limitations of Large Language Models in Information Seeking from Tables

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:14:49.634813Z

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 802f9bfa-eefc-4450-ba2a-b24836e4aa75 · outbound

This paper cites Unstructured: Open-source toolkit for ingesting and pre-processing unstructured data,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Unstructured: Open-source toolkit for ingesting and pre-processing unstructured data,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.327453Z

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 c0fcd58e-ea85-4947-85e5-3e9805dd7f2d · outbound

This paper cites {HAWatcher}:{Semantics-Aware}anomaly detection for appified smart homes,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection {HAWatcher}:{Semantics-Aware}anomaly detection for appified smart homes,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.296653Z

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 35345cdc-e370-44cb-8867-a0f6389046d4 · outbound

This paper cites Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.091345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8eadcc77-8c6a-43b2-9956-a27aa780b81a · outbound

This paper cites Leveraging Causal Information for Multivariate Timeseries Anomaly Detection,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Leveraging Causal Information for Multivariate Timeseries Anomaly Detection,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.097192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24cd879b-a6bc-48a6-b17e-77c00709fb5b · outbound

This paper cites Wadi: a water distribution testbed for research in the design of secure cyber physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Wadi: a water distribution testbed for research in the design of secure cyber physical systems,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.102977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9818cd1c-06cd-4d11-8a87-7c0e288c6e5f · outbound

This paper cites Chatgpt,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Chatgpt,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.243902Z

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 6dad53e9-decc-43cd-9514-ea1774c99cfc · outbound

This paper cites [Online].

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection [Online]

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.223327Z

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 3710133f-c246-45ce-850c-14628eb1d01c · outbound

This paper cites Deepseek chat,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Deepseek chat,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.197989Z

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 b4ac2401-1bd9-4e52-a849-d10ec47df6cf · outbound

This paper cites Stgat- mad: Spatial-temporal graph attention network for multivariate time series anomaly detection,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Stgat- mad: Spatial-temporal graph attention network for multivariate time series anomaly detection,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.178294Z

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 7019c1cd-9749-4363-98fe-f7dcae588d95 · outbound

This paper cites Graph neural network-based anomaly detection in multivariate time series,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Graph neural network-based anomaly detection in multivariate time series,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.157242Z

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 222387ba-a14a-4b17-b095-552924735c15 · outbound

This paper cites Time series anomaly detection for cyber-physical systems via neural system identification and bayesian filtering,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Time series anomaly detection for cyber-physical systems via neural system identification and bayesian filtering,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.134838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99d0865e-b713-4db4-bc38-e51d9afd3888 · outbound

This paper cites Mad-gan: Multivariate anomaly detection for time series data with generative adversarial networks,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Mad-gan: Multivariate anomaly detection for time series data with generative adversarial networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.124114Z

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 b833868a-9bb0-48c3-9401-29c56b2c07a9 · outbound

This paper cites Usad: Unsupervised anomaly detection on multivariate time series,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Usad: Unsupervised anomaly detection on multivariate time series,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.104940Z

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 a447172c-0ae5-43b3-9b73-1623bbfbe133 · outbound

This paper cites Anomaly detection in electrical substation circuits via unsupervised machine learning,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Anomaly detection in electrical substation circuits via unsupervised machine learning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.074544Z

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 684f134f-f50e-4563-a377-04ec50b83ed7 · outbound

This paper cites Log-based anomaly detection of cps using a statistical method,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Log-based anomaly detection of cps using a statistical method,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.049781Z

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 be829f7f-df36-4e1e-8f21-a6b844b68da2 · outbound

This paper cites Cyber and physical anomaly detection in smart-grids,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Cyber and physical anomaly detection in smart-grids,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.029741Z

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 1ab1d74b-c265-4f62-a5ef-f238fe1967ac · outbound

This paper cites Data-correlation-aware unsupervised deep-learning model for anomaly detection in cyber–physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Data-correlation-aware unsupervised deep-learning model for anomaly detection in cyber–physical systems,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:50.008664Z

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 927bec0e-3895-48b9-9ecb-bff512045161 · outbound

This paper cites A deep and scalable unsupervised machine learning system for cyber-attack detection in large-scale smart grids,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection A deep and scalable unsupervised machine learning system for cyber-attack detection in large-scale smart grids,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.986457Z

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 a0127ff6-05ea-4cee-bbf3-c8b461b15cbc · outbound

This paper cites Machine learning applications for anomaly detection in smart water metering networks: A systematic review,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Machine learning applications for anomaly detection in smart water metering networks: A systematic review,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.960713Z

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 fd3d89bc-25d2-40bd-95d8-d095103809fc · outbound

This paper cites An unsupervised spatiotem- poral graphical modeling approach to anomaly detection in distributed cps,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection An unsupervised spatiotem- poral graphical modeling approach to anomaly detection in distributed cps,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.941460Z

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 c54c116a-ef20-44de-b92b-fd05be554a82 · outbound

This paper cites Anomaly detection based on rbm- lstm neural network for cps in advanced driver assistance system,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Anomaly detection based on rbm- lstm neural network for cps in advanced driver assistance system,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.923105Z

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 5bc6433a-8515-48e0-8dbc-8f821cb8bc6b · outbound

This paper cites Siamese neural network based few-shot learning for anomaly detection in industrial cyber-physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Siamese neural network based few-shot learning for anomaly detection in industrial cyber-physical systems,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.899620Z

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 e35380f5-9292-430c-8faa-481a7fc0f495 · outbound

This paper cites Anomaly detection in cyber-physical systems using recurrent neural networks,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Anomaly detection in cyber-physical systems using recurrent neural networks,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.867744Z

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 5429bdba-0a3b-401b-98d3-de293a100dc2 · outbound

This paper cites An integrated framework for privacy-preserving based anomaly detection for cyber- physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection An integrated framework for privacy-preserving based anomaly detection for cyber- physical systems,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.842540Z

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 bef21a96-6f26-49aa-922a-21938531d5c4 · outbound

This paper cites Iadf-cps: Intelligent anomaly detection framework towards cyber physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Iadf-cps: Intelligent anomaly detection framework towards cyber physical systems,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.824206Z

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 71287ed5-ea96-4e58-a8b6-d4b9703333c1 · outbound

This paper cites Detecting Hallucinated Content in Conditional Neural Sequence Generation.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Detecting Hallucinated Content in Conditional Neural Sequence Generation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.218740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f8df183-afcd-4f47-9017-293e91143569 · outbound

This paper cites Mst-gat: A multimodal spatial–temporal graph attention network for time series anomaly detection,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Mst-gat: A multimodal spatial–temporal graph attention network for time series anomaly detection,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.799142Z

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 765960b0-027e-4dbd-918e-38d09f23615b · outbound

This paper cites Granger causality for time-series anomaly detection,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Granger causality for time-series anomaly detection,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.773906Z

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 22dcb981-1c3a-438c-916a-fbc99af30b4f · outbound

This paper cites Learning sparse latent graph representations for anomaly detection in multivariate time series,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Learning sparse latent graph representations for anomaly detection in multivariate time series,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.234276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6d97bfa-ca34-4369-943d-4d32f6c8d156 · outbound

This paper cites Causal discovery from temporal data: An overview and new perspectives,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Causal discovery from temporal data: An overview and new perspectives,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.239823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0369d39-4d0f-40d9-aeeb-5fcfc15cd59e · outbound

This paper cites Video Anomaly Detection and Explanation via Large Language Models.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Video Anomaly Detection and Explanation via Large Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.245285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5ec4639-fbe7-4ddd-97a8-7db42b4d96ff · outbound

This paper cites Semantic anomaly detection with large language models,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Semantic anomaly detection with large language models,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.250797Z

Source-reported events for the cited work

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Observation fd215f15-818a-44a2-9787-88d1e21e5847 · outbound

This paper cites VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.256655Z

Source-reported events for the cited work

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Observation c9d99c71-0d93-481f-a88c-ce8d1a05c2a1 · outbound

This paper cites To assess the potential and capabilities of large language models (llms) trained on in-domain ophthalmology data.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection To assess the potential and capabilities of large language models (llms) trained on in-domain ophthalmology data

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.737593Z

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 cde2ab5b-caa0-48a3-9826-93e1b13dda08 · outbound

This paper cites Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.268696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c6dc325-19ea-4661-b357-09172557ef4b · outbound

This paper cites Enhancing automatic modulation recog- nition for iot applications using transformers,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Enhancing automatic modulation recog- nition for iot applications using transformers,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.275408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1195027-c190-45e4-be6a-e325f793b082 · outbound

This paper cites Assuring llm- enabled cyber-physical systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Assuring llm- enabled cyber-physical systems,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.703467Z

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 57c02fc8-4cd9-450e-9858-91b1a8801997 · outbound

This paper cites Penetrative ai: Making llms comprehend the physical world,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Penetrative ai: Making llms comprehend the physical world,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.287026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95939395-0e98-4b5f-aafa-52f62db0a4e2 · outbound

This paper cites Llm4plc: Harnessing large language models for verifiable programming of plcs in industrial control systems,.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Llm4plc: Harnessing large language models for verifiable programming of plcs in industrial control systems,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:49.657253Z

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 2f964e57-62eb-4a41-93fa-64d4c938c98b · outbound

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

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.297936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32d32ffa-27a8-4efe-b084-0fa307655715 · outbound

This paper cites VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching.

INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:49.304233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 3959ae85-4cb6-4322-b35f-be8417642859 · inbound

Exploring Pose-Based Anomaly Detection for Retail Security: A Real-World Shoplifting Dataset and Benchmark cites this paper.

Exploring Pose-Based Anomaly Detection for Retail Security: A Real-World Shoplifting Dataset and Benchmark INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T21:00:10.623030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83afe6c9-5b2c-4302-9ccb-0929478418c2 · inbound

BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos cites this paper.

BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T20:41:24.293334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27f16198-d24a-4e01-aa50-80f685c4c6dc · inbound

Cyber-Physical Systems Security: A Comprehensive Review of Anomaly Detection Techniques cites this paper.

Cyber-Physical Systems Security: A Comprehensive Review of Anomaly Detection Techniques INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:22:24.840798Z

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 6c339477-df82-45e2-af8e-05e654fa731c · inbound

Detecting Zero-Day Web Attacks with an Ensemble of LSTM, GRU, and Stacked Autoencoders cites this paper.

Detecting Zero-Day Web Attacks with an Ensemble of LSTM, GRU, and Stacked Autoencoders INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T11:59:40.473768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75de73e0-4ef0-4608-b89b-2c82480c529d · inbound

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs cites this paper.

GOBench: Benchmarking Geometric Optics Generation and Understanding of MLLMs INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:21.444549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a6eab87-0cdc-43fa-b920-63ad6d32b64b · inbound

System-aware contextual digital twin for ICS anomaly diagnosis cites this paper.

System-aware contextual digital twin for ICS anomaly diagnosis INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:06:17.129575Z

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 abd36ee6-c7f1-472f-a764-2ecb3a02bd03 · inbound

Context Contamination in LLM Analysis of Network Security Logs: Poison with Passive Prompt Injection and Mitigation Evaluation cites this paper.

Context Contamination in LLM Analysis of Network Security Logs: Poison with Passive Prompt Injection and Mitigation Evaluation INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T01:59:39.815323Z

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Unavailable: canonical work link unavailable.