Paper Citation Record · LEDGER

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2505.06636.

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

pith.paper-citation-record.v1
2505.06636 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:42:26.931338Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy30
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f701e653-91cd-4347-8f5d-131bbad8fa90 · outbound

This paper cites Internet of robotic things intelligent connectivity and platforms,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of robotic things intelligent connectivity and platforms,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.662142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 44b9e044-52f2-43a3-adcf-904908e0e763 · outbound

This paper cites Multi- objective resource allocation for edge cloud based robotic workflow in smart factory,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Multi- objective resource allocation for edge cloud based robotic workflow in smart factory,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.646223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 41025a09-b43b-432d-a0fe-4681223a8a14 · outbound

This paper cites Internet of robotic things– converging sensing/actuating, hyperconnectivity, artificial intelligence and iot platforms,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of robotic things– converging sensing/actuating, hyperconnectivity, artificial intelligence and iot platforms,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.630595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1565b416-7a7d-4f41-9cc4-5058b42bf52b · outbound

This paper cites A novel multi-module integrated intrusion detection system for high-dimensional imbalanced data,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A novel multi-module integrated intrusion detection system for high-dimensional imbalanced data,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.615391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 50b8bfdb-3a24-4d73-acc8-56d2d439332b · outbound

This paper cites Big data manage- ment algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the internet of robotic things,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Big data manage- ment algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the internet of robotic things,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.596928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b43fa2bc-3ea9-4e9f-aa68-1a94d6988640 · outbound

This paper cites Automatic robot manoeuvres detection using computer vision and deep learning techniques: a perspective of internet of robotics things (iort),.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Automatic robot manoeuvres detection using computer vision and deep learning techniques: a perspective of internet of robotics things (iort),

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.578048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fd8971ed-ed7d-4f15-95e8-cbf106912feb · outbound

This paper cites Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A system- atic review,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A system- atic review,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.560853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72cbaf64-b947-4c0b-bdd8-40fe78591ef0 · outbound

This paper cites Attack and anomaly detection in iot sensors in iot sites using machine learning approaches,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Attack and anomaly detection in iot sensors in iot sites using machine learning approaches,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.543038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 461e51b6-45c1-4fb1-be82-d6c82012fd80 · outbound

This paper cites Internet of things intrusion detection: Centralized, on-device, or federated learning?.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of things intrusion detection: Centralized, on-device, or federated learning?

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.522339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ce82b4f1-eeba-4dca-8d7a-4791de04019a · outbound

This paper cites Communication- efficient learning of deep networks from decentralized data,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Communication- efficient learning of deep networks from decentralized data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.496542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 62a68ef9-8647-417f-88ad-4a4f3a7a7b92 · outbound

This paper cites Unsupervised data augmentation for consistency training,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Unsupervised data augmentation for consistency training,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.472336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 53f44bcc-083e-4c7d-b4b1-54ee1a439a73 · outbound

This paper cites Mixmatch: A holistic approach to semi-supervised learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Mixmatch: A holistic approach to semi-supervised learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.454132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 63212abf-5e42-4f2b-ab33-564351ec6158 · outbound

This paper cites Fixmatch: Simplifying semi- supervised learning with consistency and confidence,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Fixmatch: Simplifying semi- supervised learning with consistency and confidence,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.435499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bffdd539-0fe7-4f72-be67-212026379f68 · outbound

This paper cites Federated cycling (fedcy): Semi-supervised federated learning of surgical phases,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Federated cycling (fedcy): Semi-supervised federated learning of surgical phases,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.419082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7dc2e81c-8c68-4983-9685-61c1ce512e19 · outbound

This paper cites Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:26.819526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd023e6b-0067-4618-a910-59441e281002 · outbound

This paper cites Improving semi-supervised federated learning by reducing the gradient diversity of models,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Improving semi-supervised federated learning by reducing the gradient diversity of models,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.402467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8172724e-4678-4093-8439-e9b8274d2e50 · outbound

This paper cites FedCon: A Contrastive Framework for Federated Semi-Supervised Learning.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:26.829101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb7e5c6d-f29b-471f-812b-f7c9659d5f73 · outbound

This paper cites A simple frame- work for contrastive learning of visual representations,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A simple frame- work for contrastive learning of visual representations,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:26.834302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dc25a2e-48a8-4486-a37d-197ab80840d7 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Bootstrap your own latent-a new approach to self-supervised learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.373736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f64546ab-d214-4ddc-a3aa-5ce5a6cdcbf2 · outbound

This paper cites Perfect Alignment May be Poisonous to Graph Contrastive Learning.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Perfect Alignment May be Poisonous to Graph Contrastive Learning

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:42:26.994555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2a5aa01a-5648-4b52-8f57-685ef96c2c1d · outbound

This paper cites SimCSE: Simple Contrastive Learning of Sentence Embeddings.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things SimCSE: Simple Contrastive Learning of Sentence Embeddings

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:26.848421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee644ab4-9e90-499c-bd80-a23701dc206e · outbound

This paper cites A detailed analysis of the kdd cup 99 data set,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A detailed analysis of the kdd cup 99 data set,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:26.853512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cf49843-fb85-482e-9ae5-3e7e993c43fd · outbound

This paper cites A smart anomaly-based intrusion detection system for the internet of things (iot) network using gwo–pso–rf model,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A smart anomaly-based intrusion detection system for the internet of things (iot) network using gwo–pso–rf model,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.343065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 662a5ae1-dfb3-4d3f-820f-920cec1e6339 · outbound

This paper cites Machine learning-driven intru- sion detection for contiki-ng-based iot networks exposed to nsl-kdd dataset,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Machine learning-driven intru- sion detection for contiki-ng-based iot networks exposed to nsl-kdd dataset,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.326801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dcaa01e1-1dc8-4332-b8d4-7616eb7d8032 · outbound

This paper cites Anomaly-based intrusion detection system for iot application,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Anomaly-based intrusion detection system for iot application,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.303323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ae08323b-e5f0-457d-a455-9aa3a61d1fa9 · outbound

This paper cites Iot intrusion detection using machine learning with a novel high performing feature selection method,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Iot intrusion detection using machine learning with a novel high performing feature selection method,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.284664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7a91cf87-1d96-415b-b6f0-a0023dd175a1 · outbound

This paper cites Uids: a unified intrusion detection system for iot environment,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Uids: a unified intrusion detection system for iot environment,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.267298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d04008bc-cdfc-465f-8b1e-52648b8ada24 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Momentum contrast for unsupervised visual representation learning,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:26.882665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79c8e883-ecc8-4ef7-a239-47dbfef29012 · outbound

This paper cites Visualizing data using t-sne.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Visualizing data using t-sne

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T22:42:26.887438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1eb0790e-1081-4d20-84e6-a065c30ff12e · outbound

This paper cites Temporal ensembling for semi-supervised learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Temporal ensembling for semi-supervised learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.230023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d879e53e-b40d-41c0-a706-b2bc8403afa3 · outbound

This paper cites On convergence of fedprox: Local dissimilarity invariant bounds, non-smoothness and beyond,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things On convergence of fedprox: Local dissimilarity invariant bounds, non-smoothness and beyond,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.211287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ae937533-3284-4f50-b7df-a06d2b42d2f4 · outbound

This paper cites Intrusion detection system for nsl-kdd dataset using convolutional neural networks,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Intrusion detection system for nsl-kdd dataset using convolutional neural networks,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.191304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e251b527-dec9-4b51-b50c-e111c3fa515f · outbound

This paper cites A soft actor-critic reinforcement learning algorithm for network intrusion detection,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A soft actor-critic reinforcement learning algorithm for network intrusion detection,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.172727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 38561716-3d10-4f5c-9535-f4e3db34506d · outbound

This paper cites Gan augmen- tation to deal with imbalance in imaging-based intrusion detection,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Gan augmen- tation to deal with imbalance in imaging-based intrusion detection,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.154221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cd128543-e521-4d80-ab5f-da4c29083ce9 · outbound

This paper cites A two stage lightweight approach for intrusion detection in internet of things,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A two stage lightweight approach for intrusion detection in internet of things,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.138204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1d91f054-a643-4ab2-875d-63282f0505a6 · outbound

This paper cites Optimized intrusion detection in iot and fog computing using ensemble learning and advanced feature selection,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Optimized intrusion detection in iot and fog computing using ensemble learning and advanced feature selection,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.122030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f20f4d5b-5c67-443b-b0e2-f58787d0a418 · outbound

This paper cites A multiscale intrusion detection system based on pyramid depthwise separable convolution neural network,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A multiscale intrusion detection system based on pyramid depthwise separable convolution neural network,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.076250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6ae0d931-8146-4c40-8cde-18d5aedec0da · outbound

This paper cites A deep learning approach for intrusion detection systems in cloud computing environments,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A deep learning approach for intrusion detection systems in cloud computing environments,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:42:27.059377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.