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Paper Citation Record · LEDGER

Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:1812.02765.

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

pith.paper-citation-record.v1
1812.02765 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:45:43.458824Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-16T22:31:19.437413Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 19284d63-8152-49b9-90f5-1e7cb5e78f5a · inbound

Safety Monitoring of Machine Learning Perception Functions: a Survey cites this paper.

Safety Monitoring of Machine Learning Perception Functions: a Survey Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 105

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unresolved
no resolver link, observed 2026-08-11T19:45:43.458824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:45:43.458824Z digest=sha256:ceb9253a62f47832d670248d4e42908045bcccf988750ef1acf3bf9ab399a397

Observation a6c3ae20-c890-4fe0-a9a8-92417b9c2f43 · inbound

UN-DETR: Promoting Objectness Learning via Joint Supervision for Unknown Object Detection cites this paper.

UN-DETR: Promoting Objectness Learning via Joint Supervision for Unknown Object Detection Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 6

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unresolved
no resolver link, observed 2026-08-11T16:19:59.498878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T16:19:59.498878Z digest=sha256:4d14818ba960011cf670cb9373a489f4411bbe8c08b02c9b8da8a452114b0127

Observation 70aa4591-a38b-49ad-9c2b-0cec8eb80d07 · inbound

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation cites this paper.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 11

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unresolved
no resolver link, observed 2026-08-11T15:40:08.130172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:40:08.130172Z digest=sha256:9df312fc142c4e668bf4f8813412bfe5d637c7fadadb61bec726cbd9e5e43ade

Observation 6f2fe857-c270-4710-bea8-9a7735e8375c · inbound

Autoencoders for Anomaly Detection are Unreliable cites this paper.

Autoencoders for Anomaly Detection are Unreliable Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 15

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unresolved
no resolver link, observed 2026-08-10T15:37:16.670128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:37:16.670128Z digest=sha256:3a4a298194a426aa80466a0a5817e33849b52548513b013bd66e5f38699749e3

Observation bf98e38b-5b06-46ae-9131-cf302a61715b · inbound

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection cites this paper.

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 3

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unresolved
no resolver link, observed 2026-08-07T00:23:09.532884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:23:09.532884Z digest=sha256:1d5586c3ff799ce2e3ae0d63b04f672afd1cfad712f51a593a28c18571eab6e5

Observation fd4d4268-bd4c-4a98-ab55-86cce5e37496 · inbound

Out-of-Distribution Detection in Medical Imaging via Diffusion Trajectories cites this paper.

Out-of-Distribution Detection in Medical Imaging via Diffusion Trajectories Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T10:53:50.701826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:53:50.701826Z digest=sha256:d34fefe22d61801971737d85e1d7156d253018d53023145266a393c1039c2f5f

Observation 788ba62a-808c-44f2-a66c-7f090895dfdc · inbound

Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned cites this paper.

Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 2012

Resolution
unresolved
no resolver link, observed 2026-08-04T22:55:28.410900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:55:28.410900Z digest=sha256:62c1176bb0d0cb7b74088035c629376be59791050597950b59f273d0b9a7d85d

Observation e078fa69-1e30-40d0-86b6-e2373713b9c3 · inbound

Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive Scoring cites this paper.

Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive Scoring Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 7

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metadata mismatch
local_arxiv, observed 2026-05-16T22:31:19.439367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-16T22:28:41.134253Z digest=sha256:0248d6300fe411fc0e074413d0b934ac367ab3fefd2e0fbfd1190867f3f787d4

Observation 57da3e22-75ca-4196-a819-62c51daf004d · inbound

VOLTA: The Surprising Ineffectiveness of Auxiliary Losses for Calibrated Deep Learning cites this paper.

VOLTA: The Surprising Ineffectiveness of Auxiliary Losses for Calibrated Deep Learning Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 3

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verified exact
arxiv_id, observed 2026-05-11T05:36:01.483751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T18:02:12.278733Z digest=sha256:a026bc3cf8098b90b63482954bb12690d3e4d0bcc5bc5a22810fad9550fe7386

Observation d5d8dce6-b7a8-4a79-8d38-248de5db8419 · inbound

Unifying Runtime Monitoring Approaches for Safety-Critical Machine Learning: Application to Vision-Based Landing cites this paper.

Unifying Runtime Monitoring Approaches for Safety-Critical Machine Learning: Application to Vision-Based Landing Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 9

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metadata mismatch
arxiv_id, observed 2026-05-12T09:21:26.079382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T11:15:35.175436Z digest=sha256:3ec9ce84a6facdbf4e44bc15865ffcc16a06dcc28fad0c3dd7019be599c532f2

Observation 150dcba7-da8d-4a1a-a867-dfd67f4d7360 · inbound

HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning cites this paper.

HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 62

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metadata mismatch
arxiv_id, observed 2026-05-11T19:36:15.103228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-08T11:25:01.780099Z digest=sha256:e2da2e0e4ea756d3aacb2c294ebaf17ef1efeb065afd965f675273351a4155f3

Observation 2e110b2c-dbde-4906-82fc-e89c0c836a48 · inbound

Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning cites this paper.

Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 35

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metadata mismatch
arxiv_id, observed 2026-05-12T07:41:49.339376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-12T02:17:25.783688Z digest=sha256:3267481f516f5e3b65992200e525592bfed94f79f80d45466b69b53718665cd4

Observation 42d58488-6e80-403c-8c3e-08da69bb5ee2 · inbound

Fine-Grained Open-Set Fault Diagnosis via Metric-Guided Time-Frequency Configuration Selection and Class-Specific Autoencoders cites this paper.

Fine-Grained Open-Set Fault Diagnosis via Metric-Guided Time-Frequency Configuration Selection and Class-Specific Autoencoders Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T05:30:14.153406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:30:14.153406Z digest=sha256:26d7a755f5e11af45386c8f42c8fbb7341688562a61cd0f08004e9d262ac88e6