Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T10:53:15.301193Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2601.08480.
A citation records a reference. It does not transfer a finding from one paper to another.
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Source: paper_references, paper_reference_links, observed 2026-08-03T10:53:15.301193Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
49 of 49 outbound references displayed
External citation measurements
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Observation 5e8526a1-c69e-438a-afc5-6d7198620660 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Scream and gunshot detection and localization for audio-surveillance systems,
Reference 1
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Observation 8fa653d5-ae2a-4c4a-8b4f-24741e488929 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection De- tection and analysis of abnormal situations through fear-type acoustic manifestations,
Reference 2
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Observation c99c4a3b-3622-4e43-86e0-b3f0bf9268d9 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Unsu- pervised detection of anomalous sound based on deep learning and the neyman–pearson lemma,
Reference 3
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Observation f52fce91-bc0a-4d1b-9f8b-bbe3154a1268 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection A review on machinery di- agnostics and prognostics implementing condition-based maintenance,
Reference 4
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Observation b6c34ccf-d6d4-4ee6-9e79-8fa71a4e0a97 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Description and discussion on DCASE2020 challenge task2: Unsuper- vised anomalous sound detection for machine condition monitoring,
Reference 5
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Observation 5718a6e2-a031-4033-bbff-e3bb22e03ff4 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Complementary set varia- tional autoencoder for supervised anomaly detection,
Reference 6
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Observation efbd312f-b85c-42b9-819f-d68f6979414d · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Non-linear prediction with lstm recurrent neural networks for acoustic novelty detection,
Reference 7
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Observation d2610646-b6f2-4095-b093-fe24a4260d3d · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Self-supervised classification for detecting anomalous sounds,
Reference 8
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Observation 31511e8e-af1d-480e-a3a5-e545ec109926 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Self-supervised acoustic anomaly detec- tion via contrastive learning,
Reference 9
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Observation ec2e9d71-f241-45ce-bdb2-2508b67ded4f · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Activity-Guided Industrial Anomalous Sound Detection against Interferences
Reference 10
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Observation 5691b6d5-4546-410e-b730-cc70ce106ec1 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection A novel application of deep transfer learning with audio pre-trained models in pump audio fault detection,
Reference 11
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Observation 24a28d11-3273-45fa-a0ea-a967e96a8267 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional lstm neural networks,
Reference 12
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Observation f3ed4689-96ab-41a5-8b7b-49e826837863 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Arcface: Additive angular margin loss for deep face recognition,
Reference 13
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Observation 5b827828-3910-4788-ab31-a4e234bf4d69 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Revisiting self-supervised visual representation learning,
Reference 14
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Observation 90828c70-e1f2-43a1-ac36-a57b40c2d037 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection A simple unified framework for detecting out-of-distribution samples and adversarial attacks,
Reference 15
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Observation 9d423bea-326d-425e-b43d-1f38802de24c · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Events detection for an audio- based surveillance system,
Reference 16
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Observation 7890bfb9-35a3-420b-9f0c-29ae9907e6c9 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Audio surveillance of roads: A system for detecting anomalous sounds,
Reference 17
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Observation 1016bafe-3599-4d4f-8e6a-d1c07b398373 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Recognizing Abnormal Heart Sounds Using Deep Learning
Reference 18
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Observation 24d7589c-8a3e-409e-9a0b-97267928fcb6 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Fault detection and diagnosis of railway point machines by sound analysis,
Reference 19
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Observation 659a2cf5-63d9-467f-b14b-23bba1d72530 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection A multimodal anomaly detector for robot-assisted feeding using an lstm-based variational autoencoder,
Reference 20
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Observation 7f9defed-f1e5-4f0a-ab53-4c47598b0855 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection ToyAD- MOS: A dataset of miniature-machine operating sounds for anomalous sound detection,
Reference 21
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Observation f24bb5f8-8460-4674-8f1d-3170a4a09f1e · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection MIMII dataset: Sound dataset for malfunctioning industrial machine investigation and inspection,
Reference 22
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Observation 663b2e59-e319-4357-bf0f-00369bb7641a · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Toyadmos2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions,
Reference 23
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Observation 050f4d3e-1758-47bb-ae56-e38653faf4d2 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Description and discussion on DCASE 2022 challenge task 2: Unsu- pervised anomalous sound detection for machine condition monitoring applying domain generalization techniques,
Reference 24
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Observation 380aa6f8-f39f-4d92-a353-e1277cebf38b · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Transformer-based autoencoder with id constraint for unsupervised anomalous sound detection,
Reference 25
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Observation f63e9c23-073d-4af1-b11d-c525683c9a3b · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Anomalous sound detection with ensemble of autoencoder and binary classification approaches,
Reference 26
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Observation 7199a168-9c59-4fda-9d98-fd80b4c52aa0 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Representational learning for an anomalous sound detection system with source separation model,
Reference 27
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Observation 8bf480b2-0959-4fc5-ba75-49637823b091 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Unsupervised anomalous sound detection for industrial monitoring based on arcface classifier and gaussian mixture model,
Reference 28
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Observation de0b3a5b-b77b-47e8-8793-1bf25830badc · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Why do angular margin losses work well for semi-supervised anomalous sound detection?
Reference 29
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Observation 2a8fed5b-2892-43c9-b388-f1660851ff19 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection A simple framework for contrastive learning of visual representations,
Reference 30
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Observation b9aaa0dc-cc30-4576-939b-9661aa2098df · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Exploring simple siamese representation learning,
Reference 31
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Observation 2b552eca-84b7-4ff2-ada7-bb6a2dcb0a03 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Anomalous sound detection using audio representation with machine id based contrastive learning pretraining,
Reference 32
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Observation 0ee47b9f-1b44-48b2-b38b-b9af80c234d7 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection BEATs: Audio Pre-Training with Acoustic Tokenizers
Reference 33
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Observation 0b193d5c-c354-413f-8ed2-36dd74c775ae · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection EAT: Self-Supervised Pre-Training with Efficient Audio Transformer
Reference 34
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Observation 05b140bd-36d8-4c5f-a632-3f7619062f00 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Pre-trained model enhanced anomalous sound detection system for dcase2025 task2,
Reference 35
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Observation 4c8ee683-b006-431d-a634-2e56f7503cd6 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Genrep for first-shot unsupervised anomalous sound detection of dcase 2025 challenge,
Reference 36
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Observation cf5e2469-0322-4c8c-85df-899fe957e6c3 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Visualizing data using t-sne,
Reference 37
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Observation 159af56c-312a-4521-837f-41825984a113 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Reference 38
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Observation 0655eb43-bfe3-498d-b4a5-96f13125a585 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Understanding intermediate layers using linear classifier probes
Reference 39
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Observation caf8345d-081a-47f0-83aa-c4ad92d1a411 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Designing and Interpreting Probes with Control Tasks
Reference 40
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Observation 1cd4409b-6532-4885-b15d-6ea0b61c280c · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Understanding contrastive representation learning through alignment and uniformity on the hypersphere,
Reference 41
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Observation a78ec001-86dc-41a9-b3ab-554aa859077c · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection How well do self- supervised models transfer?
Reference 42
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Observation 01d390fa-b12a-495c-b79c-3512ab03f178 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Decoupled Weight Decay Regularization
Reference 43
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Observation dbf6a055-3dc8-4338-aa32-8d69101f3bd4 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Deep residual learning for image recognition,
Reference 44
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Observation c3ada480-c975-437d-b928-ccb846f885b4 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Anomalous sound detection based on sound separation,
Reference 45
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Observation c77b0073-61be-4b19-a038-8b49a9cef8e7 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Cmgan: Conformer-based metric- gan for monaural speech enhancement,
Reference 46
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Observation b7ed76d1-8450-405e-a152-e2aee50d8257 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Conformer: Convolution-augmented transformer for speech recognition,
Reference 47
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Observation 7c785015-5b80-44c1-941a-b44a2ad0318a · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Audio set: An ontology and human- labeled dataset for audio events,
Reference 48
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Observation e10cf1f7-46b9-4df9-be82-9fc306f31b32 · outbound
Quantitative Analysis of Proxy Tasks for Anomalous Sound Detection Sdr–half-baked or well done?
Reference 49
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No inbound Pith citation observations are available.