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Paper Citation Record · LEDGER

Practitioners' Expectations on Log Anomaly Detection

As of 18 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 1 inbound Pith citation observation for arXiv:2412.01066.

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

pith.paper-citation-record.v1
2412.01066 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:46:07.358662Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:31:15.112673Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T17:31:15.206794Z

Reference resolution

68 of 68 outbound references displayed

  • verified exact1
  • verified fuzzy42
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ec6a23fc-82a5-4fd7-a791-8bfdfb209b46 · outbound

This paper cites Using evolutionary annotations from change logs to enhance program comprehension,.

Practitioners' Expectations on Log Anomaly Detection Using evolutionary annotations from change logs to enhance program comprehension,

Reference 1

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raw_fallback, observed 2026-08-12T04:46:08.433178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.000694Z digest=sha256:cd5d0202a73bbdbaa9764fca4ac97adad9022f5496c1bf7b50f442bcb2431d04

Observation eb8d9959-3f89-451a-8609-4daab3e72996 · outbound

This paper cites On the temporal relations between logging and code,.

Practitioners' Expectations on Log Anomaly Detection On the temporal relations between logging and code,

Reference 2

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raw_fallback, observed 2026-08-12T04:46:08.414112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.006871Z digest=sha256:9becdb8a212a4ba93eddf01d792f1a2d6c7ab39643e3595800f19c22248870bc

Observation ddbd7551-f525-4077-89ea-4ceb537b07b7 · outbound

This paper cites Log-based anomaly detection without log parsing,.

Practitioners' Expectations on Log Anomaly Detection Log-based anomaly detection without log parsing,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.014515Z digest=sha256:8f9ab5633af7e833327198e757d278ed7011d0cc9c9201747a25b07fce4a884f

Observation 3540ef2f-4a6a-49ed-8685-17c7150f9083 · outbound

This paper cites Loganomaly: Unsupervised detection of sequential and quantitative anomalies in unstructured logs.

Practitioners' Expectations on Log Anomaly Detection Loganomaly: Unsupervised detection of sequential and quantitative anomalies in unstructured logs

Reference 4

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no resolver link, observed 2026-08-12T04:46:07.019947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.019947Z digest=sha256:72a3a68892954ebe291e73fc5e51eb0a7f40e021eca0f61af5454c1331082e41

Observation cce5b710-9155-4db7-9573-a12ec7772563 · outbound

This paper cites Heteroge- neous anomaly detection for software systems via semi-supervised cross- modal attention,.

Practitioners' Expectations on Log Anomaly Detection Heteroge- neous anomaly detection for software systems via semi-supervised cross- modal attention,

Reference 5

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raw_fallback, observed 2026-08-12T04:46:08.366047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.025110Z digest=sha256:38f79b826991cbaf21eab9b055404d459dd4c14d9ec5ba86e87d2683032005f8

Observation e401cf43-ba03-4db1-a705-81f9411526f0 · outbound

This paper cites Deeplog: Anomaly detection and diagnosis from system logs through deep learning,.

Practitioners' Expectations on Log Anomaly Detection Deeplog: Anomaly detection and diagnosis from system logs through deep learning,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.349156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.030288Z digest=sha256:3611dc397b5a086aefba106c0940f96ee03aab3e76329476eb0df7eed02c8ec2

Observation d423210f-06ae-48be-a5f2-c63d2f46e2cb · outbound

This paper cites Pathidea: Improving information retrieval-based bug localization by re-constructing execution paths using logs,.

Practitioners' Expectations on Log Anomaly Detection Pathidea: Improving information retrieval-based bug localization by re-constructing execution paths using logs,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.331424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.036020Z digest=sha256:44fa5dc1d462a8abec3790de7b7a201816c235b6b9c153cf0f09a8446ba84c45

Observation 69208ebe-fb3b-4fc0-8226-c1f6ffa7fff2 · outbound

This paper cites Latent error prediction and fault localization for microservice applications by learning from system trace logs,.

Practitioners' Expectations on Log Anomaly Detection Latent error prediction and fault localization for microservice applications by learning from system trace logs,

Reference 8

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no resolver link, observed 2026-08-12T04:46:07.041750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.041750Z digest=sha256:6f724901c9bff3e582b96cb698b2bf4c835a50d43bd5399e1601c29888dd090a

Observation 5e445215-cfe1-4cde-839c-2dc9e842e41d · outbound

This paper cites Deep learning or classical machine learning? an empirical study on log-based anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Deep learning or classical machine learning? an empirical study on log-based anomaly detection,

Reference 9

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no resolver link, observed 2026-08-12T04:46:07.047138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.047138Z digest=sha256:0ca97deec9386adf1de649e4255977a10766e14cea122aa131bc77a418a29bef

Observation 6ec6f597-624c-4f8f-9690-be2659a5ca37 · outbound

This paper cites Log-based anomaly detection with deep learning: How far are we?.

Practitioners' Expectations on Log Anomaly Detection Log-based anomaly detection with deep learning: How far are we?

Reference 10

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no resolver link, observed 2026-08-12T04:46:07.052608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.052608Z digest=sha256:8b1bb88228f97418a10d7752bbf72ce5e652cf3b5dcfe21f1007bb93f765a1c5

Observation abbca9b8-47dc-4e17-8f0f-060d90c0a005 · outbound

This paper cites Leavy, Research design: Quantitative, qualitative, mixed methods, arts-based, and community-based participatory research approaches.

Practitioners' Expectations on Log Anomaly Detection Leavy, Research design: Quantitative, qualitative, mixed methods, arts-based, and community-based participatory research approaches

Reference 11

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raw_fallback, observed 2026-08-12T04:46:08.280834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.057618Z digest=sha256:67e97bb9ab8a240c48d7bb5bc83b24ec71c76aad073249745d818df7ead9bc5d

Observation 001de88a-3ec6-4c12-be09-91f18e4bf040 · outbound

This paper cites Spencer, Card sorting: Designing usable categories.

Practitioners' Expectations on Log Anomaly Detection Spencer, Card sorting: Designing usable categories

Reference 12

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no resolver link, observed 2026-08-12T04:46:07.063021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.063021Z digest=sha256:7481fe03ee20e7f21b4a3ee55104e90f37ab72a0f2947507d017d074326b50b7

Observation 9d8910b5-172e-4337-83ab-ec477cd15134 · outbound

This paper cites Google forms,.

Practitioners' Expectations on Log Anomaly Detection Google forms,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.242404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.071462Z digest=sha256:f63a366d72a505f6cf6a9bd61bf0f60952f87ee197dbe3f48d887d98b5a19dba

Observation 68f8c7a3-e6ae-46f8-a538-06bd4689a69a · outbound

This paper cites Survey form,.

Practitioners' Expectations on Log Anomaly Detection Survey form,

Reference 14

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raw_fallback, observed 2026-08-12T04:46:08.224314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.077950Z digest=sha256:3eba823c5fc83e60175c861191ff3b679ad637dbd5223dd65fd6004e912230e1

Observation 3dcbf1b1-fa78-44fe-a924-2df3053ddc4b · outbound

This paper cites Wenjuanxing software,.

Practitioners' Expectations on Log Anomaly Detection Wenjuanxing software,

Reference 15

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raw_fallback, observed 2026-08-12T04:46:08.208682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.083763Z digest=sha256:2e17d169be5fb554965645963194ba2ed1617f14d1f67424996a1975817aa6c0

Observation 8879ec69-e7f5-4d0c-a83d-bb4f698059ca · outbound

This paper cites A survey of per- formance optimization for mobile applications,.

Practitioners' Expectations on Log Anomaly Detection A survey of per- formance optimization for mobile applications,

Reference 16

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raw_fallback, observed 2026-08-12T04:46:08.193450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.091731Z digest=sha256:3b437430cbf23cc26033a63e546b3631c17e4e3bda7288f8be5a1a8a82bcd791

Observation 0acadce8-c539-43a0-aac2-73c736291f67 · outbound

This paper cites On the use of evaluation measures for defect prediction studies,.

Practitioners' Expectations on Log Anomaly Detection On the use of evaluation measures for defect prediction studies,

Reference 17

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raw_fallback, observed 2026-08-12T04:46:08.177009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.097476Z digest=sha256:ae6edfffbd6da754cd65c7a7a536690d91a2c879288e7aaf26d7c9a6a89f85c3

Observation cf538b18-25eb-487c-aa6f-54425deeb6e4 · outbound

This paper cites Guidelines for snowballing in systematic literature studies and a replication in software engineering,.

Practitioners' Expectations on Log Anomaly Detection Guidelines for snowballing in systematic literature studies and a replication in software engineering,

Reference 18

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no resolver link, observed 2026-08-12T04:46:07.102680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.102680Z digest=sha256:c7c3af7ee0826fd026c43d54fa8d4f9ae358013f22229cf3e3e1918c5a3b2e63

Observation 438d7855-9f77-4d79-a1cf-ca4a6f292480 · outbound

This paper cites Logformer: A pre-train and tuning pipeline for log anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Logformer: A pre-train and tuning pipeline for log anomaly detection,

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.108405Z digest=sha256:590b4e523188ac8c6f1910435aa08154e90ee631f245f854f15635e01d1baebf

Observation 6a0c00a2-552d-468b-a73b-67beb358955f · outbound

This paper cites Onelog: towards end-to-end software log anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Onelog: towards end-to-end software log anomaly detection,

Reference 20

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no resolver link, observed 2026-08-12T04:46:07.114093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.114093Z digest=sha256:6c6ffbabb7a052516a4a2415bab0f6ad6b34febadd94baa124846754e3721d0c

Observation 0e7a64c9-ba1f-4b3f-8730-7fc39c4c74ad · outbound

This paper cites LogSD: Detecting Anomalies from System Logs through Self-supervised Learning and Frequency-based Masking.

Practitioners' Expectations on Log Anomaly Detection LogSD: Detecting Anomalies from System Logs through Self-supervised Learning and Frequency-based Masking

Reference 21

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local_arxiv, observed 2026-08-12T04:46:07.442373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.119601Z digest=sha256:7bed09b24570b46e973543a275c47ce9dac5164079de23a1aebfc8e8ccd2b8bc

Observation 42c76bb7-1539-4ab3-ba22-29132c2f08db · outbound

This paper cites Metalog: Generalizable cross-system anomaly detection from logs with meta-learning,.

Practitioners' Expectations on Log Anomaly Detection Metalog: Generalizable cross-system anomaly detection from logs with meta-learning,

Reference 22

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no resolver link, observed 2026-08-12T04:46:07.124990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.124990Z digest=sha256:72fd37b8a1e6f2371f768b8b8eabd56f359def22c511626d198c28afc822c390

Observation 804705fc-8d7a-4042-98d5-4b09ff5e8ae0 · outbound

This paper cites Semi- supervised and unsupervised anomaly detection by mining numerical workflow relations from system logs,.

Practitioners' Expectations on Log Anomaly Detection Semi- supervised and unsupervised anomaly detection by mining numerical workflow relations from system logs,

Reference 23

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raw_fallback, observed 2026-08-12T04:46:08.109644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.130012Z digest=sha256:1b4a5a725ccb84d9a77e0206dc7c340489dcad5ebd3562cf1955dca71ad3ada2

Observation c1e35dff-576b-42c8-a871-c2bbb4585ae9 · outbound

This paper cites Logonline: A semi-supervised log-based anomaly detector aided with online learning mechanism,.

Practitioners' Expectations on Log Anomaly Detection Logonline: A semi-supervised log-based anomaly detector aided with online learning mechanism,

Reference 24

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raw_fallback, observed 2026-08-12T04:46:08.092477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.134858Z digest=sha256:d3420d55e1f7b6790de9466f90ec3e2afca0c837262b22fa17fb19208681eccd

Observation 84786c5c-aff2-431b-818e-bc860bb3d2cb · outbound

This paper cites Twin graph-based anomaly detection via attentive multi-modal learning for microservice system,.

Practitioners' Expectations on Log Anomaly Detection Twin graph-based anomaly detection via attentive multi-modal learning for microservice system,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.075740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.139506Z digest=sha256:18cac7465441493f9bb9966fbae505903001242f65e3a7a97534d29e9332b952

Observation 4d8f5ef1-2e65-4538-ba27-42af14f90140 · outbound

This paper cites Loader: A log anomaly detector based on transformer,.

Practitioners' Expectations on Log Anomaly Detection Loader: A log anomaly detector based on transformer,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.056326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.144600Z digest=sha256:671bc867e21efb6701b65ec475d1e519e10045fe12e31a940082e8085027804c

Observation 56cb1180-3171-4400-b5ee-28dea16ba730 · outbound

This paper cites Mlog: Mogrifier lstm-based log anomaly detection approach using semantic representation,.

Practitioners' Expectations on Log Anomaly Detection Mlog: Mogrifier lstm-based log anomaly detection approach using semantic representation,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.037676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.149033Z digest=sha256:6a4d66a2767e2dfeac640f935ea1e14c14b73c532a1989e7d5712f51dd960214

Observation 24bf8559-7b4c-4df7-8c4b-ff4a054fd789 · outbound

This paper cites Autolog: A log sequence synthesis framework for anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Autolog: A log sequence synthesis framework for anomaly detection,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.021383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.154304Z digest=sha256:2c451d325c5f14661a1aa4a1e3e4f5ce3adb0fdab7264cbfa5486b942815541d

Observation b63edacd-ef75-4e5a-89df-21c8db8667bb · outbound

This paper cites Deepuserlog: Deep anomaly detection on user log using semantic analysis and key-value data,.

Practitioners' Expectations on Log Anomaly Detection Deepuserlog: Deep anomaly detection on user log using semantic analysis and key-value data,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:08.004888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.159205Z digest=sha256:7043667666f7a95f031e63782fcca7ceb3089e9cd35198be0c57b7c15ebcbe76

Observation b2700b69-c1c4-4c7e-95ee-84dbc69b5485 · outbound

This paper cites Logrep: Log-based anomaly detection by representing both semantic and numeric informa- tion in raw messages,.

Practitioners' Expectations on Log Anomaly Detection Logrep: Log-based anomaly detection by representing both semantic and numeric informa- tion in raw messages,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.986852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.164875Z digest=sha256:593f7df4aceb1523288b68e69c0ab89e70dcae3fd8d882f755d4f01b1f1faa03

Observation 77cc0ad8-c261-4f5a-910e-e4a95a702a0f · outbound

This paper cites Sialog: detecting anomalies in software execution logs using the siamese network,.

Practitioners' Expectations on Log Anomaly Detection Sialog: detecting anomalies in software execution logs using the siamese network,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.970409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.169211Z digest=sha256:5059348ff0b7db67262a1e44b26264ce126b30806e1c2e3a64bc782bd76ba266

Observation 28bad069-6c5f-49d0-9dfe-d6a9cc09c8b9 · outbound

This paper cites Deeptralog: Trace-log combined microservice anomaly de- tection through graph-based deep learning,.

Practitioners' Expectations on Log Anomaly Detection Deeptralog: Trace-log combined microservice anomaly de- tection through graph-based deep learning,

Reference 32

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unresolved
no resolver link, observed 2026-08-12T04:46:07.174136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.174136Z digest=sha256:a9cc09c61d569f1aa7638921a1dcbfaf014677ebadb098e59bd5140bfccf5d5b

Observation 3765072c-7527-419a-80dc-f03dcd87d0e9 · outbound

This paper cites An empirical investigation of practical log anomaly detection for online service systems,.

Practitioners' Expectations on Log Anomaly Detection An empirical investigation of practical log anomaly detection for online service systems,

Reference 33

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no resolver link, observed 2026-08-12T04:46:07.178957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.178957Z digest=sha256:fb580165be61d082e285ead8d1f715be63e5ea97dfa1b0d94a0b4d05da30c1da

Observation e879bb0c-4afb-40f6-a67b-9f9fb23a862b · outbound

This paper cites Semi-supervised log-based anomaly detection via probabilistic label estimation,.

Practitioners' Expectations on Log Anomaly Detection Semi-supervised log-based anomaly detection via probabilistic label estimation,

Reference 34

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no resolver link, observed 2026-08-12T04:46:07.184074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.184074Z digest=sha256:d3196e506d9cd03c9d3b1f998a4be10ad2e5670a389dc8439f0877d3fc93fae1

Observation d328c9ee-6952-4c07-93cf-173ad5a64fab · outbound

This paper cites Logflash: Real-time streaming anomaly detection and diagnosis from system logs for large-scale software systems,.

Practitioners' Expectations on Log Anomaly Detection Logflash: Real-time streaming anomaly detection and diagnosis from system logs for large-scale software systems,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.919192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.188894Z digest=sha256:c6beeb665722334a3233cab0cd25e7d59267ed1f0dd34f8461ca322bef86f765

Observation 878ced35-ecb9-4207-8b22-59aee55cb720 · outbound

This paper cites Logtransfer: Cross-system log anomaly detection for software systems with transfer learning,.

Practitioners' Expectations on Log Anomaly Detection Logtransfer: Cross-system log anomaly detection for software systems with transfer learning,

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.194360Z digest=sha256:7d118cff1be5e1cef85d717f31e261bfc06a7948b83fe7eb82356ccc0fe87059

Observation b094f391-379e-4a3c-98c9-e93304ea6098 · outbound

This paper cites Swisslog: Robust and unified deep learning based log anomaly detection for diverse faults,.

Practitioners' Expectations on Log Anomaly Detection Swisslog: Robust and unified deep learning based log anomaly detection for diverse faults,

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.198862Z digest=sha256:e3b26d5e063053ca6149300d4dcdc0e586ea81726edc1be27bd7821c7f438ffd

Observation 5d5fa85a-89f3-4955-852d-1972ef092633 · outbound

This paper cites Robust log-based anomaly detection on unstable log data,.

Practitioners' Expectations on Log Anomaly Detection Robust log-based anomaly detection on unstable log data,

Reference 38

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no resolver link, observed 2026-08-12T04:46:07.203871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.203871Z digest=sha256:f828324fcd179ef1b16b32ee880d0a6960878eeb53c37618ad59405cce58ac14

Observation 398dd990-0071-4c96-b215-e900c0baeb7e · outbound

This paper cites Self- attentive classification-based anomaly detection in unstructured logs,.

Practitioners' Expectations on Log Anomaly Detection Self- attentive classification-based anomaly detection in unstructured logs,

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.866680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.209185Z digest=sha256:d192755290f6c64c0f6d1aada5d24f4a4881bd2b9dba349e6198bc4b30e499b5

Observation 300e442e-f1fc-404b-a0ee-cef23e479774 · outbound

This paper cites Multi-scale one-class recurrent neural networks for discrete event sequence anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Multi-scale one-class recurrent neural networks for discrete event sequence anomaly detection,

Reference 40

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.214333Z digest=sha256:397f51a666d5f085034a6080f588dfc830d291eaab10e3ded77711aa3adb66eb

Observation 1e37e111-4167-47d6-8273-5f563bd24a41 · outbound

This paper cites Cat: beyond efficient transformer for content-aware anomaly detection in event sequences,.

Practitioners' Expectations on Log Anomaly Detection Cat: beyond efficient transformer for content-aware anomaly detection in event sequences,

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.836755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.219001Z digest=sha256:9353c7e55a7b2b91e18e9b0988600d17dc0a36f29a9b87d536c263608a010bf2

Observation d5f2383c-3b60-416e-9989-806d517e3fff · outbound

This paper cites An approach for anomaly diagnosis based on hybrid graph model with logs for distributed services,.

Practitioners' Expectations on Log Anomaly Detection An approach for anomaly diagnosis based on hybrid graph model with logs for distributed services,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.817609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.223523Z digest=sha256:c5495a63bf41ae01490abee400b46dd2a579c405ec92efda7a43740862b98207

Observation e3be9a89-a545-4fc0-a33d-af9459ac9e24 · outbound

This paper cites Aclog: An approach to detecting anomalies from system logs with active learning,.

Practitioners' Expectations on Log Anomaly Detection Aclog: An approach to detecting anomalies from system logs with active learning,

Reference 43

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no resolver link, observed 2026-08-12T04:46:07.228363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.228363Z digest=sha256:df7a690430e5cbb1d66bc0cecff19cbee9634773f067c1439f4b7abc5da282ba

Observation 941ae3be-3f30-48c5-b57d-214f83f95a00 · outbound

This paper cites Improving log-based anomaly detection with component-aware analysis,.

Practitioners' Expectations on Log Anomaly Detection Improving log-based anomaly detection with component-aware analysis,

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.789216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.233370Z digest=sha256:8e02288b1a30f6e37037d3701f1e18d90228807a818177a9bb130b9284e6bdf1

Observation 651d5f0c-aa29-4958-a814-0f90b1656fd5 · outbound

This paper cites Maddc: Multi-scale anomaly detection, diagnosis and correction for discrete event logs,.

Practitioners' Expectations on Log Anomaly Detection Maddc: Multi-scale anomaly detection, diagnosis and correction for discrete event logs,

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.772848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.238631Z digest=sha256:541ffd795762ec685fa3e9dfeffda7bdc48dad06b03826a1a8d32bdbc577a432

Observation 76d9d5c4-b1db-44ce-98b4-1218e2b6c964 · outbound

This paper cites Log sequence anomaly detection based on local information extraction and globally sparse transformer model,.

Practitioners' Expectations on Log Anomaly Detection Log sequence anomaly detection based on local information extraction and globally sparse transformer model,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.752178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.244122Z digest=sha256:8a25043d72cee9f933ed7ee73c7489ab8f4c2493805b3fb8fd5e4244910f72d0

Observation 2cd9c1e4-912a-4d6a-b87d-bc3b2db5f2dd · outbound

This paper cites Logclass: Anomalous log iden- tification and classification with partial labels,.

Practitioners' Expectations on Log Anomaly Detection Logclass: Anomalous log iden- tification and classification with partial labels,

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.732266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.249626Z digest=sha256:02918ebf6fc259d2a3bfed0d1c5c60939e6984b68e6fbe69934952a36042a76e

Observation 9e1a4ba0-0110-42c3-ad94-d5bff7275069 · outbound

This paper cites Try with simpler–an evaluation of improved principal component anal- ysis in log-based anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Try with simpler–an evaluation of improved principal component anal- ysis in log-based anomaly detection,

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.715561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.254395Z digest=sha256:ddc095017bcf7423c7abac44a524895c17634cfee8ea2abc7f8160e83a34725d

Observation 7326685c-f5a6-41cd-8742-7acb5a8cec22 · outbound

This paper cites Unsupervised log message anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Unsupervised log message anomaly detection,

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.699793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.259749Z digest=sha256:69ac2402d1855b75ecbb030139f4376640e265e3ea20457937d09d8071830449

Observation e39add08-b97f-423c-ae60-4b56c76dbc33 · outbound

This paper cites Automatic abnormal log detection by analyzing log history for providing debugging insight,.

Practitioners' Expectations on Log Anomaly Detection Automatic abnormal log detection by analyzing log history for providing debugging insight,

Reference 50

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.685018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.265245Z digest=sha256:41fc2292b8bd424c380b0e164ada61e1d25ef3ec3ee2164a688d6a7597d47da9

Observation 30d0854d-5c90-4544-86ae-89872bb5159d · outbound

This paper cites Detecting large-scale system problems by mining console logs,.

Practitioners' Expectations on Log Anomaly Detection Detecting large-scale system problems by mining console logs,

Reference 51

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.670220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.270327Z digest=sha256:699aae08cace59a3f7efed370a73545517c78b8e5923faf0f637068883ee66e4

Observation 70dcd14b-38ba-4591-bea6-9d5625d690de · outbound

This paper cites What supercomputers say: A study of five system logs,.

Practitioners' Expectations on Log Anomaly Detection What supercomputers say: A study of five system logs,

Reference 52

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no resolver link, observed 2026-08-12T04:46:07.276792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.276792Z digest=sha256:aa1de5b3211932f786ca82bab93d9e076fb3e8b19a14a328f42b64b7268310ed

Observation 3e96da08-352b-4b06-8488-6362a47e0f33 · outbound

This paper cites Software testing with large language models: Survey, landscape, and vision,.

Practitioners' Expectations on Log Anomaly Detection Software testing with large language models: Survey, landscape, and vision,

Reference 53

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unresolved
no resolver link, observed 2026-08-12T04:46:07.281447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.281447Z digest=sha256:a2177c3b7b27501360c5825e7156525d45517fab41c59b866e960bda761af485

Observation 68d60cd6-1152-4ed0-948d-c7f83b296620 · outbound

This paper cites Evaluating large language models in class-level code generation,.

Practitioners' Expectations on Log Anomaly Detection Evaluating large language models in class-level code generation,

Reference 54

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no resolver link, observed 2026-08-12T04:46:07.286451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.286451Z digest=sha256:168c94092dede1174eff66afad09a19486df09cc501d7c81033fbd25f24ce244

Observation 916c64de-f655-4626-b3db-134507bf2738 · outbound

This paper cites Large Language Models for Software Engineering: Survey and Open Problems.

Practitioners' Expectations on Log Anomaly Detection Large Language Models for Software Engineering: Survey and Open Problems

Reference 55

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no resolver link, observed 2026-08-12T04:46:07.291543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.291543Z digest=sha256:475f134530e1ffb31c7e47e2f19cf1e573a177502d8541662725f83135d5c4c7

Observation dae2ee2a-2a49-4cb5-9725-7b705cc1108b · outbound

This paper cites Practitioners' Expectations on Code Completion.

Practitioners' Expectations on Log Anomaly Detection Practitioners' Expectations on Code Completion

Reference 56

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no resolver link, observed 2026-08-12T04:46:07.296841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.296841Z digest=sha256:7e469c2fa5b3337781f93ef3cdd519fcabde540fab90c7ed8f7a7076a726108b

Observation 8f0b6af3-4c21-493c-8ba6-78969d3ec13b · outbound

This paper cites A language model for statements of software code,.

Practitioners' Expectations on Log Anomaly Detection A language model for statements of software code,

Reference 57

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no resolver link, observed 2026-08-12T04:46:07.302529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.302529Z digest=sha256:bde5d7c6a671304ed143b86e94c053b08d28b903ca1cadaa7f4c76e459d4f645

Observation af5cf7f6-e045-47fe-a69b-0e9c821296ac · outbound

This paper cites Failure prediction in ibm bluegene/l event logs,.

Practitioners' Expectations on Log Anomaly Detection Failure prediction in ibm bluegene/l event logs,

Reference 58

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.614640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.307618Z digest=sha256:153ea590841c5786f45ac405efd2b7160471c5f75f6a4b1a90224e74b0c2bca0

Observation 3d9c28ca-3b24-4445-b84b-83224d3c7090 · outbound

This paper cites Automated it system failure prediction: A deep learning approach,.

Practitioners' Expectations on Log Anomaly Detection Automated it system failure prediction: A deep learning approach,

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.598957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.312366Z digest=sha256:a00b878d54341e070a1cff46a1b627e292e16b2ef990747f65ec8b48a4dfbf03

Observation 5e879c45-5ece-42d7-bddf-d67147822c4d · outbound

This paper cites Long short-term memory based operation log anomaly detection,.

Practitioners' Expectations on Log Anomaly Detection Long short-term memory based operation log anomaly detection,

Reference 60

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.583272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.317774Z digest=sha256:de87acc28b2703c623d93af88fba996340ad0f5ee780450c6c0ab42980cf1c53

Observation 6e806bb9-9155-4b3e-b43c-6f7043572d18 · outbound

This paper cites Detecting anomaly in big data system logs using convolutional neural network,.

Practitioners' Expectations on Log Anomaly Detection Detecting anomaly in big data system logs using convolutional neural network,

Reference 61

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unresolved
no resolver link, observed 2026-08-12T04:46:07.322677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.322677Z digest=sha256:2918ac58654ec2940af33bd64cd17464b8b208e866cdf510b05d14b2b0d54d30

Observation ac8d1bf0-7160-4692-859d-6e16e573a187 · outbound

This paper cites Log clustering based problem identification for online service systems,.

Practitioners' Expectations on Log Anomaly Detection Log clustering based problem identification for online service systems,

Reference 62

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no resolver link, observed 2026-08-12T04:46:07.327595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.327595Z digest=sha256:dd9a5ea0da86cabdae629e0533ac4389589c74f04d8c5946ecc409fa8fe1f300

Observation b7054927-a060-420e-8902-689c9a624a41 · outbound

This paper cites Lanobert: System log anomaly detection based on bert masked language model,.

Practitioners' Expectations on Log Anomaly Detection Lanobert: System log anomaly detection based on bert masked language model,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.546490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.332907Z digest=sha256:424bb47a8501449f0c4b136272b93dd66c1ed7cc3c554fa099ec2de54cbf19ff

Observation 6a792a2f-7ec1-49d9-8642-3e17a010e22c · outbound

This paper cites Are they all good? studying practitioners’ expectations on the readability of log messages,.

Practitioners' Expectations on Log Anomaly Detection Are they all good? studying practitioners’ expectations on the readability of log messages,

Reference 64

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.528124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.338374Z digest=sha256:dda56d42e2280080f78caf6372ca1c2bbabb0f8f222b6a2e2708f50b755bf0b6

Observation effcbaef-ffa7-43cf-a6c1-d20317391ce6 · outbound

This paper cites An interview study about the use of logs in embedded software engineering,.

Practitioners' Expectations on Log Anomaly Detection An interview study about the use of logs in embedded software engineering,

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.511430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.342740Z digest=sha256:85797e155001529b5da6611c82d9d3a9bd8243d6e82bce35270fc4070435c1c1

Observation bf9ba1a4-aa70-43bc-a163-78bb71d5d74d · outbound

This paper cites How do developers’ profiles and experiences influence their logging practices? an empirical study of industrial practitioners,.

Practitioners' Expectations on Log Anomaly Detection How do developers’ profiles and experiences influence their logging practices? an empirical study of industrial practitioners,

Reference 66

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.494270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.347042Z digest=sha256:0caa4371549b24e96faab9d667a325978222ef5a907cea6755c9ca8854208d2e

Observation 9ab6105c-6086-4491-89cc-38ac06741488 · outbound

This paper cites A survey on automated log analysis for reliability engineering,.

Practitioners' Expectations on Log Anomaly Detection A survey on automated log analysis for reliability engineering,

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.476100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.353029Z digest=sha256:21820d70b12db0162443c6888388be207b58895c692d0f4a8f80f25954fc16fe

Observation 5b8a03c4-bcd5-49eb-a964-be9eb3cee6bc · outbound

This paper cites Where do developers log? an empirical study on logging practices in industry,.

Practitioners' Expectations on Log Anomaly Detection Where do developers log? an empirical study on logging practices in industry,

Reference 68

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verified fuzzy
raw_fallback, observed 2026-08-12T04:46:07.459110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T04:46:07.358662Z digest=sha256:c9a52b1cdd8750c616bb4ddc194089e8df0fa3bc7eb770b280c28e6c82cdbdb5

Pith citing papers

Observation 17258b18-0158-4615-be35-82f6054d9f85 · inbound

Beyond Window-Based Detection: A Graph-Centric Framework for Discrete Log Anomaly Detection cites this paper.

Beyond Window-Based Detection: A Graph-Centric Framework for Discrete Log Anomaly Detection Practitioners' Expectations on Log Anomaly Detection

Reference 2018

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verified exact
local_arxiv, observed 2026-08-10T17:31:15.215206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T17:31:15.112673Z digest=sha256:66e3e8d3c7e751fb29ee96df9c91073b241cc7e72ed53a7f53991a01f5f6f2ff