Paper Citation Record · LEDGER

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning

As of 24 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 2 inbound Pith citation observations for arXiv:2506.19246.

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

pith.paper-citation-record.v1
2506.19246 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:37:04.412940Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:08:45.973761Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:48:41.235540Z

Reference resolution

23 of 23 outbound references displayed

verified exact1
verified fuzzy16
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69483654-e1da-453f-b197-b0790162d405 · outbound

This paper cites A survey of graph-based deep learning for anomaly detection in distributed systems,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning A survey of graph-based deep learning for anomaly detection in distributed systems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.706939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4919fe8e-216f-425e-9206-17236500e0c5 · outbound

This paper cites A Reinforcement Learning Approach to Traffic Scheduling in Complex Data Center Topologies,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning A Reinforcement Learning Approach to Traffic Scheduling in Complex Data Center Topologies,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.695205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 94283618-2884-4032-803d-2a714b018958 · outbound

This paper cites Distributed anomaly detection in smart grids: a federated learning-based approach,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Distributed anomaly detection in smart grids: a federated learning-based approach,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.682591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eb2ca5e3-1a20-417d-b69c-e2c8dbce1836 · outbound

This paper cites DAD: A Distributed Anomaly Detection system using ensemble one-class statistical learning in edge networks,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning DAD: A Distributed Anomaly Detection system using ensemble one-class statistical learning in edge networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.670492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4ce01ea6-dcde-4ed3-b2f0-b8a0fb2fb344 · outbound

This paper cites Host-based IDS: A review and open issues of an anomaly detection system in IoT,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Host-based IDS: A review and open issues of an anomaly detection system in IoT,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.657451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2dca9a33-50dc-422d-b17e-dcaa305a4eea · outbound

This paper cites Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T18:37:04.347452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5609c616-e82c-44ab-9af6-e438973e5ed3 · outbound

This paper cites Self-Attention-Based Modeling of Multi-Source Metrics for Performance Trend Prediction in Cloud Systems,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Self-Attention-Based Modeling of Multi-Source Metrics for Performance Trend Prediction in Cloud Systems,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T18:37:04.352247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a238702-207d-4f50-9e2d-8c292f1ec3e5 · outbound

This paper cites A comprehensive study of anomaly detection schemes in IoT networks using machine learning algorithms,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning A comprehensive study of anomaly detection schemes in IoT networks using machine learning algorithms,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.637566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 77b021dd-71e8-4708-bfef-d19d6dc4409a · outbound

This paper cites Self- Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Self- Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T18:37:04.359413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d384c2b9-6a03-40e4-853d-ce3d62647fd7 · outbound

This paper cites Distributed anomaly detection using concept drift detection based hybrid ensemble techniques in streamed network data,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Distributed anomaly detection using concept drift detection based hybrid ensemble techniques in streamed network data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.618405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 02740f5d-d693-43f4-9d35-732c93c05bbc · outbound

This paper cites Security and privacy-enhanced federated learning for anomaly detection in IoT infrastructures,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Security and privacy-enhanced federated learning for anomaly detection in IoT infrastructures,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.605399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0798eb15-5964-457e-ace9-91b04ba34d38 · outbound

This paper cites Light-weight federated learning-based anomaly detection for time-series data in industrial control systems,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Light-weight federated learning-based anomaly detection for time-series data in industrial control systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.592732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fcfe5d33-3e97-4f2d-8bad-330d87d29bdb · outbound

This paper cites Topology-aware decision making in distributed scheduling via multi-agent reinforcement learning,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Topology-aware decision making in distributed scheduling via multi-agent reinforcement learning,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T18:37:04.374325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50523165-d443-4fef-a892-79212eccbd6c · outbound

This paper cites Continuous Control-Based Load Balancing for Distributed Systems Using TD3 Reinforcement Learning,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Continuous Control-Based Load Balancing for Distributed Systems Using TD3 Reinforcement Learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.572219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6c4d290c-2d9b-43a7-acb3-957ccd3933c8 · outbound

This paper cites Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Intelligent Task Scheduling for Microservices via A3C-Based Reinforcement Learning

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:37:04.466338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 97df7d48-d969-43d5-95d0-ded69ef6a698 · outbound

This paper cites Graph Neural Network-Based Collaborative Perception for Adaptive Scheduling in Distributed Systems.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Graph Neural Network-Based Collaborative Perception for Adaptive Scheduling in Distributed Systems

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T18:37:04.385594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 482e69a9-ac07-4059-a860-3e5b9983c1bd · outbound

This paper cites Distributed network traffic scheduling via trust-constrained policy learning mechanisms,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Distributed network traffic scheduling via trust-constrained policy learning mechanisms,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T18:37:04.389698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 339cf3ee-c716-48d1-a63b-1bac9ddcedec · outbound

This paper cites Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.551559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ef7f8093-a8e2-4f81-85af-4378e56a666c · outbound

This paper cites Temporal-Spatial Deep Learning for Memory Usage Forecasting in Cloud Servers.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Temporal-Spatial Deep Learning for Memory Usage Forecasting in Cloud Servers

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.539057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ad426771-cfce-465e-aba3-8b4580e4fe02 · outbound

This paper cites Multivariate Time Series Forecasting Through Automated Feature Extraction and Transformer-Based Modeling,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Multivariate Time Series Forecasting Through Automated Feature Extraction and Transformer-Based Modeling,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.527480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ed063389-0d46-4a1b-8434-ed661da864f8 · outbound

This paper cites Bold but cautious: Unlocking the potential of personalized federated learning through cautiously aggressive collaboration,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Bold but cautious: Unlocking the potential of personalized federated learning through cautiously aggressive collaboration,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.515372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dce9abba-161b-4ec2-85f0-9a388e6767ca · outbound

This paper cites Model-contrastive federated learning,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Model-contrastive federated learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.503191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d89a50d7-a3b3-4163-90d0-b191f2a614af · outbound

This paper cites Fedproto: Federated prototype learning across heterogeneous clients,.

Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning Fedproto: Federated prototype learning across heterogeneous clients,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:37:04.491623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation c9cbf502-f901-4a11-8368-f5c36cdeb725 · inbound

Graph Neural Network and Transformer Integration for Unsupervised System Anomaly Discovery cites this paper.

Graph Neural Network and Transformer Integration for Unsupervised System Anomaly Discovery Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T21:08:45.973761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 528ba36a-9f0b-4ce4-8d14-407236550cb1 · inbound

Topology-Aware Graph Reinforcement Learning for Dynamic Routing in Cloud Networks cites this paper.

Topology-Aware Graph Reinforcement Learning for Dynamic Routing in Cloud Networks Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:48:41.337718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.