Pith. sign in

Paper Citation Record · LEDGER

Deep Structured Cross-Modal Anomaly Detection

As of 20 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:1908.03848.

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

pith.paper-citation-record.v1
1908.03848 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:05:29.633573Z

measured 32 of 32 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

  • verified exact2
  • verified fuzzy22
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fffd0441-19bd-408f-8841-25f38a205cfe · outbound

This paper cites Anomaly detection: A survey,.

Deep Structured Cross-Modal Anomaly Detection Anomaly detection: A survey,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:30.056628Z

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=2026-08-14T14:05:29.515793Z digest=sha256:c0f834421ab450bdb303e1142ed881d7f181d73d9d90bfcd76b02903597e06f9

Observation 772cd9bd-81f7-4a39-9d07-65c26abc2e3c · outbound

This paper cites Muvir: Multi-view rare category detection.

Deep Structured Cross-Modal Anomaly Detection Muvir: Multi-view rare category detection

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:30.043053Z

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=2026-08-14T14:05:29.520351Z digest=sha256:6e66612ee0270a5955dbccfccedb448aeffb0ea0bc31b6ab850990e3c8f515a5

Observation 8100bac3-d03b-4172-b22e-c0d57bbcc865 · outbound

This paper cites A spectral framework for detecting inconsistency across multi-source object re- lationships,.

Deep Structured Cross-Modal Anomaly Detection A spectral framework for detecting inconsistency across multi-source object re- lationships,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:30.028509Z

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=2026-08-14T14:05:29.524356Z digest=sha256:875422d040a27dbd2e93152f2505d54aa972ae4473d457abcdeada3e6e8f7e93

Observation a066b221-3ac2-40e4-a6f4-5fcb657c6af1 · outbound

This paper cites Canonical correlation analysis.

Deep Structured Cross-Modal Anomaly Detection Canonical correlation analysis

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:30.015881Z

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=2026-08-14T14:05:29.528615Z digest=sha256:c4968365125cc9017d23dbfcc77bf47b9fd1eaa21807ba832db864778551fed9

Observation 1b042e9b-c20a-49e3-9561-9a897ace9bac · outbound

This paper cites Kernel and nonlinear canonical correlation analysis,.

Deep Structured Cross-Modal Anomaly Detection Kernel and nonlinear canonical correlation analysis,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.533380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.533380Z digest=sha256:4c428065a418a75913b004b8083a1b50666a93b312c937dfdf82ea4c45537345

Observation b01d6a08-9e62-45d0-952b-b4bc8a17415b · outbound

This paper cites Multi-view low-rank analysis for outlier detection,.

Deep Structured Cross-Modal Anomaly Detection Multi-view low-rank analysis for outlier detection,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.991991Z

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=2026-08-14T14:05:29.537555Z digest=sha256:45579e22b45a647538158d7665ce2597fc8dad150170a0665e192715a85f6553

Observation 2a6f9154-ee75-42d2-8dc7-43318cddbccb · outbound

This paper cites Collaborative multi-view denoising,.

Deep Structured Cross-Modal Anomaly Detection Collaborative multi-view denoising,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.976887Z

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=2026-08-14T14:05:29.541610Z digest=sha256:a029853ae436fdbd5c5de58b0912a4c68450aee3c4cc7f8a16fa5074125c0b24

Observation 99e9b04d-409c-4235-a42e-ffd98bab1153 · outbound

This paper cites Neural fraud de- tection in credit card operations,.

Deep Structured Cross-Modal Anomaly Detection Neural fraud de- tection in credit card operations,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.962722Z

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=2026-08-14T14:05:29.545408Z digest=sha256:d65e914cdd857906ebdcc59d618df1e805fe8cfa22b8a616949216847d6d61bd

Observation ecf86dda-e725-4687-828f-bd2fb59ff1bf · outbound

This paper cites A survey of data mining and machine learning methods for cyber security intrusion detection,.

Deep Structured Cross-Modal Anomaly Detection A survey of data mining and machine learning methods for cyber security intrusion detection,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.549053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.549053Z digest=sha256:f42111de11efd35d61ab0ac5aa05a2f2970a8609f637ac883735e236bf6ca36d

Observation 629cdcdd-24c3-4330-9163-f2f4f90e0b0d · outbound

This paper cites A survey on wearable sensor- based systems for health monitoring and prognosis,.

Deep Structured Cross-Modal Anomaly Detection A survey on wearable sensor- based systems for health monitoring and prognosis,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.942000Z

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=2026-08-14T14:05:29.552179Z digest=sha256:6cef41417d590bda04eadee4f49b7e3c44a72c812ec2c9f4d2dd1b7dae8c1a99

Observation 13713744-e174-457d-aeb5-50387498e057 · outbound

This paper cites Anomaly detection and classification for hyperspectral imagery,.

Deep Structured Cross-Modal Anomaly Detection Anomaly detection and classification for hyperspectral imagery,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.928334Z

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=2026-08-14T14:05:29.555256Z digest=sha256:24805bf5c4a2406a98465269ff8fec09265032a23782f3946713dcaf7e6fcdf2

Observation cb1cfa5e-4b85-4e17-9b90-1b0440b976b1 · outbound

This paper cites Combining negative selection and classification techniques for anomaly detection,.

Deep Structured Cross-Modal Anomaly Detection Combining negative selection and classification techniques for anomaly detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.915224Z

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=2026-08-14T14:05:29.558447Z digest=sha256:ebcb610db56c43513848b72441e7bf292854a48e46c876950499a3e3fd453b6b

Observation 3bfe9802-9b81-47a1-a00a-37e8531cea27 · outbound

This paper cites Intrusion detection with unlabeled data using clustering,.

Deep Structured Cross-Modal Anomaly Detection Intrusion detection with unlabeled data using clustering,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.903986Z

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=2026-08-14T14:05:29.561466Z digest=sha256:0c45abb2d05dbbd5990b71df0ec5b91cd9ae5af3fe67a9b3643e6b030b1fa4a3

Observation fa910c61-a462-4c69-93c2-69fbe84df982 · outbound

This paper cites Specae: Spectral autoen- coder for anomaly detection in attributed networks,.

Deep Structured Cross-Modal Anomaly Detection Specae: Spectral autoen- coder for anomaly detection in attributed networks,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.891006Z

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=2026-08-14T14:05:29.564734Z digest=sha256:06f30d5df11acda605c9dd12c0dff1a02d90756dafc34a6482dea503fa33ccd5

Observation f54024ef-6096-4f20-b597-7d05bc84ae0d · outbound

This paper cites Clustering- based anomaly detection in multi-view data,.

Deep Structured Cross-Modal Anomaly Detection Clustering- based anomaly detection in multi-view data,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.876869Z

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=2026-08-14T14:05:29.567819Z digest=sha256:5af9de050d54f6572894f9a729bbfd2c9b87bf51ffdb2c2c757523cc92d94206

Observation ed0a318b-568b-417e-a594-3b3aeefe3782 · outbound

This paper cites Exploiting Similarities among Languages for Machine Translation.

Deep Structured Cross-Modal Anomaly Detection Exploiting Similarities among Languages for Machine Translation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.571359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.571359Z digest=sha256:4c8eb68a73b19bd2e63c370b01aaafc2baab5cdd3654ecb2610b82f85c3c7416

Observation 6f8a77bd-6c4e-4bf1-96f0-35dc0d914a6c · outbound

This paper cites Multimodal deep learning,.

Deep Structured Cross-Modal Anomaly Detection Multimodal deep learning,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.865160Z

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=2026-08-14T14:05:29.575158Z digest=sha256:2baa72caa94e2b05dee94a335e8e1be4eff05ef4a4bc9f13120bd6bca4051add

Observation f7295599-ba26-464d-bb40-c5bbadad5dac · outbound

This paper cites Efficient learning of deep boltz- mann machines,.

Deep Structured Cross-Modal Anomaly Detection Efficient learning of deep boltz- mann machines,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.851759Z

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=2026-08-14T14:05:29.579037Z digest=sha256:5326710854ae6e88608f4338272cd5194db258e0b798b507d3cabf3d84cc2db9

Observation 24a8bec0-0178-438a-b199-751594dfbfc4 · outbound

This paper cites Speech recognition with deep recurrent neural networks,.

Deep Structured Cross-Modal Anomaly Detection Speech recognition with deep recurrent neural networks,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.839340Z

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=2026-08-14T14:05:29.582371Z digest=sha256:fbb4705e37e531e3e81a443a0d09367962ad8691f98404d80a78a7f8efcb81bf

Observation db5f7764-7a26-425f-a18d-c20ea9ffcb89 · outbound

This paper cites Graph recurrent networks with attributed random walks,.

Deep Structured Cross-Modal Anomaly Detection Graph recurrent networks with attributed random walks,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.826439Z

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=2026-08-14T14:05:29.585531Z digest=sha256:727f410ec321b9ae936acadb35a170b977dc1a8c2b38c280f466575340b21049

Observation 7a2fcdf3-ad75-475e-bb05-aee1a0afb314 · outbound

This paper cites Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding.

Deep Structured Cross-Modal Anomaly Detection Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-14T14:05:29.700834Z

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=2026-08-14T14:05:29.589707Z digest=sha256:73f9eabfd03d2f9b428dc4239155cc6c0be44d92cbd3b2e4edc5e1cac019c1e3

Observation 50b313b1-63b7-4d4d-8763-1135b144046c · outbound

This paper cites Dropout: a simple way to prevent neural networks from over- fitting,.

Deep Structured Cross-Modal Anomaly Detection Dropout: a simple way to prevent neural networks from over- fitting,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.594584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.594584Z digest=sha256:6b061000f65e43ad1b2edc8831c09f933156d51437a7aa029868bdd148527833

Observation ecf6ddd4-fc3d-489f-8885-dcee50659a9b · outbound

This paper cites MNIST handwritten digit database,.

Deep Structured Cross-Modal Anomaly Detection MNIST handwritten digit database,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.598326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.598326Z digest=sha256:81b4a0dee33bc399aae524d82656a02dd9f87285796777a51ce26a2996b47350

Observation 27ea0360-0145-4591-81a5-2912b1cc256a · outbound

This paper cites Distributed representations of words and phrases and their composi- tionality,.

Deep Structured Cross-Modal Anomaly Detection Distributed representations of words and phrases and their composi- tionality,

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.602030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.602030Z digest=sha256:50f62b5db661a8a0c7d7055a28f5cefbc4ef4c999198724dc1d07a950b114858

Observation bb44a45e-883a-4a88-95ba-5a6d5bdedea4 · outbound

This paper cites Glove: Global vectors for word representation,.

Deep Structured Cross-Modal Anomaly Detection Glove: Global vectors for word representation,

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.605686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.605686Z digest=sha256:269dabd3789f47ebe41d1631003c951076e65ae2c127e420bb76dfb09bf7cd01

Observation c6f37aa1-b41e-4730-868f-5ec43c2325ad · outbound

This paper cites A large-scale hierarchical multi- view rgb-d object dataset,.

Deep Structured Cross-Modal Anomaly Detection A large-scale hierarchical multi- view rgb-d object dataset,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.781136Z

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=2026-08-14T14:05:29.609260Z digest=sha256:5c7602d780960fbd3ec24b42786784d903bff3a4dfacbd38ec7b33e2f793c1a1

Observation 2faaa565-3b53-4c8f-a8ce-a603f05e9df8 · outbound

This paper cites A kernel method for canonical correlation analysis.

Deep Structured Cross-Modal Anomaly Detection A kernel method for canonical correlation analysis

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-14T14:05:29.613395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:05:29.613395Z digest=sha256:618c087d04fc36cba2d7f60119843ac4748af12e4b532e96b37bf2d825856c62

Observation 8204d30a-66ea-45c3-8fa5-4af98840b721 · outbound

This paper cites Partial least square regression (pls regression),.

Deep Structured Cross-Modal Anomaly Detection Partial least square regression (pls regression),

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.767656Z

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=2026-08-14T14:05:29.617712Z digest=sha256:ffc95a063852f4edf6d4cd356e6a0114863924f2fa159c0f8dda2937d1b9b487

Observation 3104f645-5a1c-43bf-9a14-d8e0c8112491 · outbound

This paper cites Learning two-branch neural networks for image-text matching tasks,.

Deep Structured Cross-Modal Anomaly Detection Learning two-branch neural networks for image-text matching tasks,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.753983Z

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=2026-08-14T14:05:29.621316Z digest=sha256:41d008cb2ce814e08c1378842b621018b688e41d322165adbb7030713a367b08

Observation c4dc4a77-a7aa-479a-947e-c05a40f4c48e · outbound

This paper cites Learning deep structure-preserving image-text embeddings,.

Deep Structured Cross-Modal Anomaly Detection Learning deep structure-preserving image-text embeddings,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.739591Z

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=2026-08-14T14:05:29.625432Z digest=sha256:5239a816bd7407d91c4b85ea00a619a7850c3396055b2d1690fa8264e96a58d2

Observation 1d43407f-28c6-481a-8758-5869b58cb498 · outbound

This paper cites Deep Structured Energy Based Models for Anomaly Detection.

Deep Structured Cross-Modal Anomaly Detection Deep Structured Energy Based Models for Anomaly Detection

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-14T14:05:29.671758Z

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=2026-08-14T14:05:29.629787Z digest=sha256:82600bccd30f841b8b7c8cf4bc153501256f130deeb98031203a8da3a41d4f92

Observation eebf73da-4c89-4ae2-b1ff-2e2ed6704193 · outbound

This paper cites Heterogeneous network embedding via deep architectures,.

Deep Structured Cross-Modal Anomaly Detection Heterogeneous network embedding via deep architectures,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:05:29.725682Z

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=2026-08-14T14:05:29.633573Z digest=sha256:88167914d35a8098c28e43fbbd8f6b402f8145400e0e8841d06e179ad7d55ec6

Pith citing papers

No inbound Pith citation observations are available.