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Paper Citation Record · LEDGER

Practitioners' Expectations on Log Anomaly Detection

As of 12 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 2026-08-12T06:34:41.77262+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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.000694Z digest=sha256:eccb05b19d2a982fe3f5252c5673efccaf7095eaf77495de8652ffdd2bf7ddaa

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.006871Z digest=sha256:55bc7997028e8015f79c861e0a5d651c7e2d4f5efd9926db82c8e10e59acfce9

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.014515Z digest=sha256:8abe92fb93868f55cba099cd5085ecdd79665f3adec9b4b36c684709cd5309eb

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.019947Z digest=sha256:a451c09ea903ee29f4a9aeba0047e9b9d6e6b0b5f89e39caab91d9196e1c069c

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.025110Z digest=sha256:b86c254d6053cb4138136aea2d0407d0c75e55d727175f500f8c097a595a68e2

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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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.030288Z digest=sha256:eadde82c7ef5117f53f2520d179313483ee696b51e37b4862e4be12e63ff08d5

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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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.036020Z digest=sha256:9b64b0cfec8be9e7f3a1a37e4159c49674166eae235e2eee39aa8f2975a84dce

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=sha256:6a263f6254708d4fc7755518d6becc4b6ec13876e7bf8aaac1f4d7c2bc8ff8a9

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.047138Z digest=sha256:056d1dccbd0f2fd8663ca717e7cafc093ad7e7c4726d45abcb3c34ac68704460

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.052608Z digest=sha256:3d387ecbb3e91f4a1ecdbe6d24f96fa7e8fc133f811d8505b8c1a482ac6c3cbc

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.057618Z digest=sha256:6a7d4a9a86a96a8b0662afccf36901f840c3c2dbf78c00a591cdea174a57bed1

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.063021Z digest=sha256:f215db511706fe795eecc018a11d8b2b20b229a14a86a67b0d1ac89bcff6b7eb

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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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.071462Z digest=sha256:3cf96c2b019381e685617f3780e4042abb5036ab2c7c41e42cf97f4b4f3fe22e

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.077950Z digest=sha256:68372df977f386e2405891d8afa67285c861011ac8b2df1f1fffea0c110df0b9

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.083763Z digest=sha256:2bb4cd366db7845fd462e6b2c5ab0af05d280fa99f5e52bcdc57001462deef0c

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.091731Z digest=sha256:e62fa65e7390bc222a5d0994fe3774d02d9e59356ad6c475960a5cf2ead73566

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.097476Z digest=sha256:f9c4cf4643463b9bc25c45cfa1a254ce60d4adee3324a06deb68d9f9f42b283e

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.102680Z digest=sha256:268d571423ac7d00247949778dcd579fca673dcef54f7b312abd8acf5b27e73c

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:de82eaa6185dc0b611d3083ee9f64e1817b97d274ba4f0b032df7da35d24dae3

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.114093Z digest=sha256:e8e94244fe786c272f0595c0becb48422cb6b6aad333f90539a2acfdcf350021

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.119601Z digest=sha256:cf31fc556a3d9e7f004b04f6c226798503b669728cc8cf11335df987dcae9f77

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:afb4839d02f232e8c07a0e2ec2d0b5e522b0441f18bb231db7911af0d25d782c

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.130012Z digest=sha256:6a2dbee36428894e339c63ca20000296db882b64901e86761e12d2b3c1a6dd6b

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.134858Z digest=sha256:d0cae0b1104ed53f6eca72fc041f4a73aee7027021c13b28d2da77efacc4743c

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.139506Z digest=sha256:5f9a76d7ebb718af22b0c195cd5ced0a982abe92550565adef0ddb168ed03313

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

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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.144600Z digest=sha256:97e56178bc0117e7f67764163a7a164dedfabbf4aae5b971e5d97925d9f6c63b

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

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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.149033Z digest=sha256:03b576505a2a62770594da6cfed34c77c5ad7758c41684606e3edd36d66b6a08

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

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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.154304Z digest=sha256:8fbe1a5df39f2be896ebc3c4d394705cc15718a2980d2e883cb2e107d8411013

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

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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.159205Z digest=sha256:cba51810feda5126e2d207cfe3a60115fef10ff054bffcedbe5bcfbd7d0d43e7

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.164875Z digest=sha256:ef7939db89d52e0df7d90d7ea94f017c25c2a01bc9731144558f253e208cc8cb

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

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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.169211Z digest=sha256:772350d9982fc76e065906a9d87b941291baea96113a27dcba7f05d0e6dd5956

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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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=sha256:1d7ef052968715b5969f3366714a9398bcc81096b682836a97fd11715583dc04

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:f9684a499e901087c6d88001a6bdc2ff8028843c711a80f4e55d6b3e7c286dd6

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=sha256:8273d6b77e465860de3c93b562be0711912a695e3d8dea339edde9b62d7faeea

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.188894Z digest=sha256:1ad1f66b62094d75c3a0104c5b4a8d6faf96d41a53f689f05d93ef1320d6491c

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.194360Z digest=sha256:3d5b07fb061695b02eb5ef3b0dae763f0155d6ac6050bacb91121a016a3203e7

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:cdd94559a16943273dee35ccacbb6656536e7c51f96d34a3594b9f691f50510a

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=sha256:8fb783a91ce8171722268e9417b18a78808fda0537b3fb1624e902ebde98b864

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.209185Z digest=sha256:becbecd8ea4abca6002eea4ed271263bc36bafea8ada28ccd93c3c995e8d2300

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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no resolver link, observed 2026-08-12T04:46:07.214333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:46:07.214333Z digest=sha256:1b65e282c989f79aed2ad72ea6e1ff33b187e0dd54c6e02ff9bbf7150bd57720

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.219001Z digest=sha256:ade75443321e949b58ea04ec5d44566d1b3bf897bb1d51dc25db825cb26e8a83

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.223523Z digest=sha256:bf78b3223f77d88cc0e36d385e148e7d8086d2e5419c23ef556987f894775183

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=sha256:2b65ced05d66ba73d58301388cff7c4c3188d099e9fedb7586b06d5b88ce5bbd

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.233370Z digest=sha256:14e5a5b564288cdf41263c5ace9b0d6b535d4a0f4fe7ce2cd4efa29ec79eeb89

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

Resolution
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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.238631Z digest=sha256:7f0c4827a079a67d73c4fa3583005ef22c1c51b89a123fd324d200952d575003

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.244122Z digest=sha256:9409c9911535a549ffa2ffad47dc120f008e3c365fc7876e510521459f6a0ed9

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

Resolution
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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.249626Z digest=sha256:e36d7f7e350f9f29bea5c790763e9d95295432c5fdd8208a2bfdec1e146a6bc9

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.254395Z digest=sha256:dcb75ce04ca531c1a077bc1d3d57909e5c1303fb83585832449c752da0c0ff30

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.259749Z digest=sha256:e9bcf4af186badf3f8bd069f2025b24c8f67801a1c6db59e07f18bc6034316f5

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.265245Z digest=sha256:a902d326db613fa0b604bbd7d6aa043d171f67efb55bf733e79405ae8ad65fdc

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.270327Z digest=sha256:1f964685087f1e73865b0dd0c3c37c5e2a6b1e2836ecb4b1dce759b4a0328a92

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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unresolved
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=sha256:601dd1bdd159f172223897ddb8a2b67dc98d735141b48703896a857356f500bb

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=sha256:783f848d4e665fe525f8164bbe4223aaf435e858a1e51827ed64692d16426bee

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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unresolved
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=sha256:7745a6927f4287682548eefd90da911a61405d44bb4c3ef86ba2bffadb42b0fa

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:f8a30e9c2c72fd967cd2fd5b056ef0af0861bc465a0e28b3490c5de53fc41b64

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=sha256:95a7d31713727f3d7c10b3fd5a8389623f40563015c87adacf278287d36168f6

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=sha256:2a7cb5314bddec67f010f48aeb6a6bcb6f156f1d40e3165d924dc96bc1e142ad

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.307618Z digest=sha256:b8ec845165c2083b992aaa80f34350bb614556f91522215c3774ae67454cc4c1

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.312366Z digest=sha256:3829266d7d31487909edad4edfa06206752ec3fc047f0b56dacc15737e5b75b3

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.317774Z digest=sha256:210b0f37adfa471fe93e870054c6d9e629fa1d84ee289bfaa0c6f481bbcfbd7c

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:a8b8ac63dbbf6f67d43a1fe8db2a81f42ff82110ac4479f6789b18c0458ec648

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:eb424d610ba21ac8e9c48fcd6e30726958a1a9a76134d5c502ec1c7e4362975e

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.332907Z digest=sha256:e9d93b25811e78dda58c2bceae692142d082143cad5be0afbe4be70c1bdfbb00

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.338374Z digest=sha256:f9449a7f45a06f2345e28568286de91cbbb0929e2313c72570608d36594d5676

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

Resolution
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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.342740Z digest=sha256:65d5412c8c215c238d2b325f645fbc50da153289cb7ad4c69cfe75a7ece6031d

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.347042Z digest=sha256:d26f7317bd795217d441644001d343c0199bd765961b6b7a71d353d2053d87e5

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.353029Z digest=sha256:316d4c8d52d995ee2dc2f8eae3eba9a3658aeaae4a4c7092ab581abf20ed6563

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:46:07.358662Z digest=sha256:e7ff158d0fb32c9e199693a11ab371c4935d6783009d466a2099d4fd0e63c9c1

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

Resolution
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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T17:31:15.112673Z digest=sha256:7c90b0a14ed952db53a8a910d2f5f57917095b4abf4d4a8f45248393da7fac39