Pith. sign in

Paper Citation Record · LEDGER

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments

As of 19 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2509.06419.

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

pith.paper-citation-record.v1
2509.06419 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:42:42.757427Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

50 of 50 outbound references displayed

  • verified exact3
  • verified fuzzy33
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 42d66948-30c6-4b26-beac-2212c249472e · outbound

This paper cites LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:39.070545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:39.070545Z digest=sha256:dcf879cd38847a7424ecb76b9e0359568ca3235ac4b62b3845bf753b15350f4a

Observation f626623f-6fe9-4da3-811f-5026544d020a · outbound

This paper cites Deep one-class classification,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Deep one-class classification,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:39.133347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:39.133347Z digest=sha256:1930f5ff76f6ca28a3794e155c5711b3287033cb665c6b041444c6ed10be1550

Observation a738dd35-8bb5-44cc-99cf-44438a252eca · outbound

This paper cites Deep contrastive one-class time series anomaly detection,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Deep contrastive one-class time series anomaly detection,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.655452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.201936Z digest=sha256:d6de70bb3eb8c4ae7a360144633edb2d1ab439014e16ee989e05e186ed5427d7

Observation 68f9ef5a-44f2-428c-8c8b-2b57f247a43b · outbound

This paper cites Deep autoencoding one-class time series anomaly detection,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Deep autoencoding one-class time series anomaly detection,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.641442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.272766Z digest=sha256:0a08a3c49442a113feadf04a100a3464a380764f1033997562bfee0a86a0102f

Observation 2bdf6d34-deb0-44c6-8b22-834091910497 · outbound

This paper cites RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated Data.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated Data

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-04T23:42:43.094832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.400684Z digest=sha256:a0c79e2e3eecee7d1e0b27dd442ed1bd37816e44e0fd2e1cf1929b51852ba2b3

Observation 642b6518-98e9-460d-a81c-82a9450a197a · outbound

This paper cites Deep anomaly detec- tion with outlier exposure,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Deep anomaly detec- tion with outlier exposure,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.627260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.457236Z digest=sha256:fa85c705c974fd6cca29b8b47bcc84c8805654c38b88469e08b6f84b407a0c0d

Observation 9be41735-de13-450d-a076-9e489bb8bb77 · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly detection and localization,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Cutpaste: Self-supervised learning for anomaly detection and localization,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:39.533699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:39.533699Z digest=sha256:92d4040e73e11cd574be615411396d1a4f3dbf28c987ec062181d1280cfd3e0e

Observation d38c6a36-1c3c-477c-b688-dc0cb381f5ec · outbound

This paper cites Deep Semi-Supervised Anomaly Detection.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Deep Semi-Supervised Anomaly Detection

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:39.606068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:39.606068Z digest=sha256:48460c3afdeda53203169c0d36bfbeb55e31687811141aa7fb8d84f9d782e2f6

Observation 46ada269-59d2-4eff-8a8e-0674b93ab553 · outbound

This paper cites Neural contextual anomaly detection for time series,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Neural contextual anomaly detection for time series,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.601640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.711131Z digest=sha256:39e5691cce9bbd103c1045f9d827f37b723495bdd490fe8b355b57a1e7682707

Observation 0db1f24e-3329-4619-90ac-d4d0e5768b46 · outbound

This paper cites AnomalyBERT: Self-Supervised Transformer for Time Series Anomaly Detection using Data Degradation Scheme.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments AnomalyBERT: Self-Supervised Transformer for Time Series Anomaly Detection using Data Degradation Scheme

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-04T23:42:43.057122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.832767Z digest=sha256:1b0a61f7d4b9edde35cd77394ddda303a44018fc9dbe2054eaae39014f9fbb88

Observation 42bf9646-ff11-49f6-ac97-9bb741a4e741 · outbound

This paper cites Revisiting time series outlier detection: Definitions and benchmarks,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Revisiting time series outlier detection: Definitions and benchmarks,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.587772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.911036Z digest=sha256:84fe07da62c068e5386601eede41fd25f3e042c2b769f1067652092f60178371

Observation 8f2b77b5-2e84-4417-bffd-5e9b2f6fc82a · outbound

This paper cites Detecting spacecraft anomalies using lstms and nonparametric dynamic thresholding,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Detecting spacecraft anomalies using lstms and nonparametric dynamic thresholding,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.574057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:39.991378Z digest=sha256:dde4ec47ff570247df95eda34482751c643247ae6773eb41398fc784bbc890a6

Observation 6313dc5d-7ec5-4baa-b693-46d019ebe263 · outbound

This paper cites Cutaddpaste: Time series anomaly detection by exploiting abnormal knowledge,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Cutaddpaste: Time series anomaly detection by exploiting abnormal knowledge,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.559162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.067837Z digest=sha256:27d5bf2347435dcbdf0640af91227ad24ddeaeb03e428f183de7fc9d523ef2b5

Observation 0b1d487e-0297-4ae2-91fe-43ec0040a567 · outbound

This paper cites Deep learning for anomaly detection: A review,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Deep learning for anomaly detection: A review,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.543712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.155258Z digest=sha256:9cbbac8354a87d6fc49a11bae72c5a3e052e39a564b1480126f754512433f3c9

Observation db4b8e3e-647c-46ba-a76f-24eaddce6d79 · outbound

This paper cites Unsupervised anomaly detection with generative adversarial networks to guide marker discovery,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Unsupervised anomaly detection with generative adversarial networks to guide marker discovery,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:40.258525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:40.258525Z digest=sha256:f5793a513d2df0eb715d794849ec3319bfcaaaf1b5e387317f64aee9e590657d

Observation 287a5f6c-6334-4570-8235-acd0811042dd · outbound

This paper cites Gan-based anomaly detection: A review,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Gan-based anomaly detection: A review,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.518516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.326037Z digest=sha256:0eee3139b6839adf13d24803a7b59e670c55b8cd5fc921cf11acde03975b5810

Observation d1cfd72b-841e-48bf-8cca-f71ee5a99976 · outbound

This paper cites Deep autoencoding gaussian mixture model for unsupervised anomaly detection,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Deep autoencoding gaussian mixture model for unsupervised anomaly detection,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.503781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.387879Z digest=sha256:91b757d2dc6e902e1c7673d7b1fdd48f2e091b193dbfcf7383f84fc4e3ebde1e

Observation e4f0e277-9163-4a61-964d-a3776a11de37 · outbound

This paper cites Learning and evaluating representations for deep one-class classification,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Learning and evaluating representations for deep one-class classification,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.489184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.464615Z digest=sha256:91226873449e32e6f97ab32904607cd80936287ac987edf45947a70bdb651a37

Observation 996ee4ad-e8ca-4eb5-9363-703d3dca51fe · outbound

This paper cites Genias: Generator for instantiating anomalies in time series,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Genias: Generator for instantiating anomalies in time series,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:40.541465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:40.541465Z digest=sha256:497ae396ab703beb6577b1ee36de6e03afdbbcf7ac6a696497070214abfa3804

Observation fdb52951-b627-4697-b3e6-b5bae1ca91df · outbound

This paper cites Robust and explainable detector of time series anomaly via augmenting multiclass pseudo- anomalies,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Robust and explainable detector of time series anomaly via augmenting multiclass pseudo- anomalies,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.474387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.667136Z digest=sha256:936cc77d6679cf8c45cbc8b32676f9f323cf49b14a7c6f7290bfb4cf1dde95c7

Observation 3df970fe-de84-440c-bc49-1e9114d9d847 · outbound

This paper cites Rethinking Assumptions in Deep Anomaly Detection.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Rethinking Assumptions in Deep Anomaly Detection

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-04T23:42:42.867499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.739969Z digest=sha256:be5f4b63db51535e7d0007dd5f24bd6d658d37e872a6d707f88b134c4cab53e1

Observation 56cf560e-d3ca-421a-ac12-bc44b0a9df79 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments mixup: Beyond Empirical Risk Minimization

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:40.816664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:40.816664Z digest=sha256:f14c63586d65bf0c7d43f6f8136b1a24a945ddc71da31f49ce35ef5dc1648663

Observation dc8c888e-bfd5-4efa-bfe8-68926f6e0694 · outbound

This paper cites Cutmix: Reg- ularization strategy to train strong classifiers with localizable features,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Cutmix: Reg- ularization strategy to train strong classifiers with localizable features,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:40.879342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:40.879342Z digest=sha256:b995a23a8251ecbe1986d4762575eb1695c4b967289dd9826e342de03ac01034

Observation 660444e6-9c79-4895-8053-186c7248e0af · outbound

This paper cites Snapmix: Semantically proportional mixing for augmenting fine-grained data,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Snapmix: Semantically proportional mixing for augmenting fine-grained data,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.450947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:40.927772Z digest=sha256:6ef19f4fca5ff4bfefde890aa7e32efc0a1652660cd20d0b6a9da4248bda1554

Observation 4da28050-ccc0-4718-b8da-7fdb2bd454d1 · outbound

This paper cites Smoothmix: Training confidence-calibrated smoothed classifiers for certified robustness,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Smoothmix: Training confidence-calibrated smoothed classifiers for certified robustness,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.436944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.056655Z digest=sha256:825f3fa699c753163703929c63bcafc6e40cb7a868bc8bb9ee29573e7128ec0c

Observation 4a63dd7b-57bf-49c8-a2ba-c7c6f3c6a1ce · outbound

This paper cites Manifold mixup: Better representations by interpolating hidden states,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Manifold mixup: Better representations by interpolating hidden states,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.422915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.084019Z digest=sha256:720c7846161bffe3a9b752cbb5670eec4d66bcc3b7930e426bff4ae3012d9c00

Observation 0a6007f4-ea9a-4ef0-a199-3f729b0441ad · outbound

This paper cites Finding order in chaos: A novel data augmentation method for time series in contrastive learning,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Finding order in chaos: A novel data augmentation method for time series in contrastive learning,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.407763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.151208Z digest=sha256:e7e1bc06769680555c8f9c2984f2556fba71cdbff799a007c2de724a8d7d2467

Observation 778b6d2a-2871-4dfa-abd9-f3624dcf95ad · outbound

This paper cites TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:41.202924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:41.202924Z digest=sha256:30903db562bdce22906b74aa431b498b708a90b91caceb1536374136ac9df564

Observation 63b44aa5-0685-466a-b240-c77a43241d51 · outbound

This paper cites Current time series anomaly detection bench- marks are flawed and are creating the illusion of progress,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Current time series anomaly detection bench- marks are flawed and are creating the illusion of progress,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.391336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.245518Z digest=sha256:7de499cb773a506e540a32cef81c857b64c1334927b39a69ad1dad5d24f8cf3b

Observation 3d5442ba-2538-401c-8457-46ec00fd4849 · outbound

This paper cites Evaluating real-time anomaly detection algorithms–the numenta anomaly benchmark,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Evaluating real-time anomaly detection algorithms–the numenta anomaly benchmark,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.377077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.325770Z digest=sha256:c02f7f5705495a0ce0dc6cd1ab4eefb61908972f3a34529ec6298020eb2d12ca

Observation 535f180b-8871-46a4-9215-c55d321108d4 · outbound

This paper cites S5 - a labeled anomaly detection dataset, version 1.0 (16m),.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments S5 - a labeled anomaly detection dataset, version 1.0 (16m),

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.362969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.457715Z digest=sha256:fa78e68ee90fc888a1912ce994b46684b2715cf80a4d4733b1f5d74b5ea1e51d

Observation 080e85c0-6470-4e11-92a3-fde14a85145c · outbound

This paper cites Robust anomaly detection for multivariate time series through stochastic recurrent neural network,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Robust anomaly detection for multivariate time series through stochastic recurrent neural network,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.348866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.539190Z digest=sha256:23b4cb678d2e8601a41a0ccaffd3300943eda09820ad5d963535dbc8740173da

Observation e22b41c9-270e-471a-8c73-7b519fba700f · outbound

This paper cites The 1st match for aiops,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments The 1st match for aiops,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.335073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.555283Z digest=sha256:d7a48ee820a8fb27c719c96afebf5902a9c839e14f4119cc9eaff07884fab9ac

Observation 61bb3ec3-4a88-4a3e-b367-58e6d032b68e · outbound

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

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Swat: A water treatment testbed for research and training on ics security,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:41.598147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:41.598147Z digest=sha256:87385fb0156dbb5c68a41d45ddb54f03bff7dea83e2faf24409f0f9a1638cbef

Observation 086c9c56-8793-445f-bd9e-6753b0b45232 · outbound

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

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Wadi: a water distribution testbed for research in the design of secure cyber physical systems,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:41.695432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:41.695432Z digest=sha256:e8191a71ccee2a231a49abe2c26aea38d927bba07ad84d4cd02f70d4d2f58f4d

Observation b260b234-7fea-4f87-9ee2-ba8530229b6b · outbound

This paper cites European Space Agency Benchmark for Anomaly Detection in Satellite Telemetry.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments European Space Agency Benchmark for Anomaly Detection in Satellite Telemetry

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:41.807316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:41.807316Z digest=sha256:6cd25ecda8b7364822c29ff55336ecb9f2fca399bcb2aaae5e5bc1fe619dd8c9

Observation 128e3afe-00b6-4ecf-b1fb-daa1d91d5280 · outbound

This paper cites Unsupervised anomaly detection via variational auto- encoder for seasonal kpis in web applications,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Unsupervised anomaly detection via variational auto- encoder for seasonal kpis in web applications,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.301795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.840172Z digest=sha256:414da3d2ccc8e146fc940422bd9712a53f5968c5fa36ad7e3c179f1b5d8b0381

Observation 908f3d8e-b0fd-44d7-88b2-c333ce7388c5 · outbound

This paper cites Towards a rigorous evaluation of time-series anomaly detection,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Towards a rigorous evaluation of time-series anomaly detection,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.287617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:41.925900Z digest=sha256:16734b3bae179bb221fab9f146278e36529cc8eceb005212dce2822f9e6677a1

Observation 933fcd9e-822b-427b-a9cc-bf6d84f0fce1 · outbound

This paper cites Local evaluation of time series anomaly detection algorithms,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Local evaluation of time series anomaly detection algorithms,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.273406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.031299Z digest=sha256:639328ae569f7d86fc119a6ae67a249bc7fb412acce67481183f7e84120c8935

Observation 286c5688-d7f7-4599-bf03-4db7339d9a29 · outbound

This paper cites Support vector method for novelty detection.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Support vector method for novelty detection

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.257437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.120137Z digest=sha256:48a1d4eac10124d76d8e7b70cac297d590f1ea1bbd68c50d16cf5e38723c2bd0

Observation 5c03d91c-dc6f-4025-b52b-1f3270c9f1e1 · outbound

This paper cites Isolation-based anomaly detection,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Isolation-based anomaly detection,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:42.188324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:42.188324Z digest=sha256:6a01a571dd4944eb2b6af2023b805b732a96ad385bc88e05b8e9cb0d96fbacfa

Observation 010a90f4-eb21-4445-995f-bd7df21c94b6 · outbound

This paper cites Robust random cut forest based anomaly detection on streams,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Robust random cut forest based anomaly detection on streams,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.233415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.281276Z digest=sha256:809f7edb8b615ed8e00e4ae5dc8fa8cb1848c3c408e01a83d9e5b0ce3ddb32c7

Observation c52fbfb3-dd2b-445a-8eba-bce784589db4 · outbound

This paper cites Time-series anomaly detection service at microsoft,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Time-series anomaly detection service at microsoft,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.219179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.421449Z digest=sha256:f71a3e7694cd1671dd6963f6a15c3dc61c0ad27001268c6e94cee5cde6723ae0

Observation 6d709677-7ab8-446b-a357-879c2c99221b · outbound

This paper cites Matrix profile xxiv: scaling time series anomaly detection to trillions of datapoints and ultra-fast arriving data streams,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Matrix profile xxiv: scaling time series anomaly detection to trillions of datapoints and ultra-fast arriving data streams,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.203639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.527910Z digest=sha256:81b0013ac9463a00a938c492095409a2a047c9d0b4bf7a1bb8cf35a851a13a2a

Observation d600aa8b-f3ce-4776-b538-3c0b052460c8 · outbound

This paper cites Time-series representation learning via temporal and contextual con- trasting,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Time-series representation learning via temporal and contextual con- trasting,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.186834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.608158Z digest=sha256:ea37fabf4e69ccd47e09d32b827f0fbc773222ef7d1c30158224f7af62d6c481

Observation 76a771b3-634d-4c9c-8478-3dd4411b9880 · outbound

This paper cites Anomaly transformer: Time series anomaly detection with association discrepancy,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Anomaly transformer: Time series anomaly detection with association discrepancy,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.172258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.712402Z digest=sha256:9a90d42844b9b9fcf8237471d92e86401f6a9d5c6a472deb0d45abee83dcd2f5

Observation 1561c1be-527a-4ebb-b7af-1a3d609d7555 · outbound

This paper cites Mixmamba: Time series modeling with adaptive expertise,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Mixmamba: Time series modeling with adaptive expertise,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.157545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.746155Z digest=sha256:6d3f145f4500c4d00739e32959e5a7370257a9a8240268b3ad2e5fc62efd82ef

Observation 4ac0db97-b850-4d28-8bf3-e80f2964e8df · outbound

This paper cites Beyond sharing: Conflict-aware multivariate time series anomaly detection,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Beyond sharing: Conflict-aware multivariate time series anomaly detection,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.141891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.749973Z digest=sha256:df96372a6b2bf5eafe7a0cac959900bec5bee8525617ca7dbb684bd590f6b9cb

Observation f6ebec6e-6d59-4087-b8b0-6b4841b9b0a3 · outbound

This paper cites Sensitivehue: Multivariate time series anomaly detection by enhancing the sensitivity to normal patterns,.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Sensitivehue: Multivariate time series anomaly detection by enhancing the sensitivity to normal patterns,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:42:43.127009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-04T23:42:42.753790Z digest=sha256:a7ddea0e5dcdc913a31ddb8ad886930068da93f84591276c7a7971b40aa96213

Observation f3a89861-60e0-4636-ba5d-8a9ed74d3933 · outbound

This paper cites Merlion: A Machine Learning Library for Time Series.

CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments Merlion: A Machine Learning Library for Time Series

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-04T23:42:42.757427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:42:42.757427Z digest=sha256:92d951fc5a53a22d5117c65db875c25d7bce325158c87fbc677e6f06432d557f

Pith citing papers

No inbound Pith citation observations are available.