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Paper Citation Record · LEDGER

Multimodal deep networks for text and image-based document classification

As of 22 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:1907.06370.

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

pith.paper-citation-record.v1
1907.06370 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T21:42:20.194268Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:09:14.760420Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T16:21:06.398788Z

Reference resolution

39 of 39 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce50bfb0-9156-4153-b6b0-653f9aa3d8d2 · outbound

This paper cites Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval.

Multimodal deep networks for text and image-based document classification Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval

Reference 1

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Observation 4df5349f-14b8-4232-b699-f67dfa415f60 · outbound

This paper cites Document Analysis System.

Multimodal deep networks for text and image-based document classification Document Analysis System

Reference 2

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Source-reported events for the cited work

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Observation 95fb7b23-ddc4-4279-82f6-009d78d255ad · outbound

This paper cites Tesseract: An Open-Source Optical Character Recognition Engine.

Multimodal deep networks for text and image-based document classification Tesseract: An Open-Source Optical Character Recognition Engine

Reference 3

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Observation 1f35c377-b2b1-4045-9a44-b2ae6b9f4f38 · outbound

This paper cites Classification of binary document images into textual or nontextual data blocks using neural network models.

Multimodal deep networks for text and image-based document classification Classification of binary document images into textual or nontextual data blocks using neural network models

Reference 4

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Source-reported events for the cited work

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Observation 071b8a6b-827f-40fc-b7b3-7012649e6db5 · outbound

This paper cites Segmentation and classification for mixed text/image documents using neural network.

Multimodal deep networks for text and image-based document classification Segmentation and classification for mixed text/image documents using neural network

Reference 5

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Source-reported events for the cited work

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Observation 18e026dc-46d8-4035-b931-8e089584f625 · outbound

This paper cites Gradient-based learning applied to document recognition.

Multimodal deep networks for text and image-based document classification Gradient-based learning applied to document recognition

Reference 6

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Source-reported events for the cited work

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Observation 1700e1fa-6b59-45b5-a9fe-eec5e149613a · outbound

This paper cites A survey of document image classification.

Multimodal deep networks for text and image-based document classification A survey of document image classification

Reference 7

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Source-reported events for the cited work

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Observation 3dcfec9f-4678-4b9e-975f-95e688b2c9fa · outbound

This paper cites Structural similarity for document image classification and retrieval.

Multimodal deep networks for text and image-based document classification Structural similarity for document image classification and retrieval

Reference 8

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Source-reported events for the cited work

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Observation cb7a34ee-e8f8-4f9f-8e21-829fb6f892bb · outbound

This paper cites Analysis of CNNs for Document Image Classification.

Multimodal deep networks for text and image-based document classification Analysis of CNNs for Document Image Classification

Reference 9

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Source-reported events for the cited work

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Observation 1e9de73b-ce5b-48ce-89d5-d9eea933ffa9 · outbound

This paper cites Cutting the Error by Half: Investigation of V ery Deep CNN and Advanced Training Strategies for Document Image Classification.

Multimodal deep networks for text and image-based document classification Cutting the Error by Half: Investigation of V ery Deep CNN and Advanced Training Strategies for Document Image Classification

Reference 10

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Source-reported events for the cited work

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Observation 74084279-2db5-49c7-a918-62aec3b3d25f · outbound

This paper cites Document Image Classification with Intra- Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks.

Multimodal deep networks for text and image-based document classification Document Image Classification with Intra- Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks

Reference 11

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Source-reported events for the cited work

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Observation 58d90e45-296e-4a95-bb4a-558bdfcf8baa · outbound

This paper cites Identity Documents Classification as an Image Classification Problem.

Multimodal deep networks for text and image-based document classification Identity Documents Classification as an Image Classification Problem

Reference 12

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Source-reported events for the cited work

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Observation 1050fe84-13d6-4363-aa37-a598014c43e7 · outbound

This paper cites dhSegment : A generic deep-learning approach for document segmentation.

Multimodal deep networks for text and image-based document classification dhSegment : A generic deep-learning approach for document segmentation

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 8e0c21a6-2daf-4ba0-a639-3055c09fb33c · outbound

This paper cites Automatic Document Classification.

Multimodal deep networks for text and image-based document classification Automatic Document Classification

Reference 14

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Source-reported events for the cited work

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Observation af32755f-3e60-4fe7-9cdf-1db20f2fdb52 · outbound

This paper cites One-Class SVMs for Document Classification.

Multimodal deep networks for text and image-based document classification One-Class SVMs for Document Classification

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation fab47132-2b3f-4c6f-b483-53c1311ef1b6 · outbound

This paper cites Statistical topic models for multi-label document classification.

Multimodal deep networks for text and image-based document classification Statistical topic models for multi-label document classification

Reference 16

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Source-reported events for the cited work

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Observation 5e34062f-1b64-4014-afec-c7568125d969 · outbound

This paper cites Efficient Estimation of W ord Representations in V ector Space.

Multimodal deep networks for text and image-based document classification Efficient Estimation of W ord Representations in V ector Space

Reference 17

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Source-reported events for the cited work

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Observation 728bb3d8-c593-4be8-ae0b-1fea80f59c78 · outbound

This paper cites Deep Contextualized W ord Representations.

Multimodal deep networks for text and image-based document classification Deep Contextualized W ord Representations

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 4444983c-48f4-4247-850c-0eea4417234f · outbound

This paper cites Hierarchical Attention Networks for Document Classification.

Multimodal deep networks for text and image-based document classification Hierarchical Attention Networks for Document Classification

Reference 19

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Source-reported events for the cited work

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Observation b0437f7d-6f6b-424a-bfe7-7b04bff4885d · outbound

This paper cites Embedded Textual Content for Document Image Classification with CNNs.

Multimodal deep networks for text and image-based document classification Embedded Textual Content for Document Image Classification with CNNs

Reference 20

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Observation d1385c50-c2b8-491e-b190-619ec6b2dd87 · outbound

This paper cites Learning to Extract Semantic Structure from Documents Using Multimodal FCNNs.

Multimodal deep networks for text and image-based document classification Learning to Extract Semantic Structure from Documents Using Multimodal FCNNs

Reference 21

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Observation 43ac49cc-0c91-480f-b3c1-4e1f8ab9b672 · outbound

This paper cites Improving Classification of an Industrial Document Image Database by Combining Visual and Textual Features.

Multimodal deep networks for text and image-based document classification Improving Classification of an Industrial Document Image Database by Combining Visual and Textual Features

Reference 22

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Observation 702aecf6-511c-4e47-af4f-399a1f674a0f · outbound

This paper cites MobileNetV2: Inverted Residuals and Linear Bottlenecks.

Multimodal deep networks for text and image-based document classification MobileNetV2: Inverted Residuals and Linear Bottlenecks

Reference 23

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Observation 89583378-a67a-469a-a32e-ac37f43f0486 · outbound

This paper cites CNN Features Off-the-Shelf: An Astounding Baseline for Recognition.

Multimodal deep networks for text and image-based document classification CNN Features Off-the-Shelf: An Astounding Baseline for Recognition

Reference 24

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Observation 1a0f3465-ebae-4a3a-abec-68892d2f024e · outbound

This paper cites Deep Residual Learning for Image Recognition.

Multimodal deep networks for text and image-based document classification Deep Residual Learning for Image Recognition

Reference 25

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Source-reported events for the cited work

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Observation 50da01c9-6cb9-45bf-8dfa-95b1b2cd3566 · outbound

This paper cites A Threshold Selection Method from Gray-Level Histograms.

Multimodal deep networks for text and image-based document classification A Threshold Selection Method from Gray-Level Histograms

Reference 26

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Observation 639a8c39-f737-4d56-b164-2fa94fb8e0ea · outbound

This paper cites Glove: Global V ectors for W ord Representation.

Multimodal deep networks for text and image-based document classification Glove: Global V ectors for W ord Representation

Reference 27

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Observation 690c46f3-db6d-4321-9fad-e78fbd42849b · outbound

This paper cites Mimicking W ord Embeddings using Subword RNNs.

Multimodal deep networks for text and image-based document classification Mimicking W ord Embeddings using Subword RNNs

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 909ed0d1-bac0-4840-8dd1-744aa625a704 · outbound

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Multimodal deep networks for text and image-based document classification Enriching W ord V ectors with Subword Information

Reference 29

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Source-reported events for the cited work

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Observation 78bbeede-d7bf-48dc-b468-7c881086080d · outbound

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Multimodal deep networks for text and image-based document classification Bag of Tricks for Efficient T ext Classification

Reference 30

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Source-reported events for the cited work

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Observation 3e348398-7aa3-44be-8aac-bb0617b90532 · outbound

This paper cites Magnitude: A Fast, Efficient Universal V ector Embedding Utility Package.

Multimodal deep networks for text and image-based document classification Magnitude: A Fast, Efficient Universal V ector Embedding Utility Package

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation ad86258e-274c-4d12-9395-7936885f6ec8 · outbound

This paper cites A Simple but T ough-to-Beat Baseline for Sentence Embeddings.

Multimodal deep networks for text and image-based document classification A Simple but T ough-to-Beat Baseline for Sentence Embeddings

Reference 32

Resolution
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Source-reported events for the cited work

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Observation 6da6105f-4c77-4059-b83e-6b0b51d0596c · outbound

This paper cites spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing.

Multimodal deep networks for text and image-based document classification spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing

Reference 33

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9ea8a753-70ad-4d11-a956-4c21208b5316 · outbound

This paper cites Multimodal deep learning for robust RGB-D object recognition.

Multimodal deep networks for text and image-based document classification Multimodal deep learning for robust RGB-D object recognition

Reference 34

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation fcb91b22-c817-446d-8dc1-e1aff7cdf5bd · outbound

This paper cites Delving Deep into Rectifiers.

Multimodal deep networks for text and image-based document classification Delving Deep into Rectifiers

Reference 35

Resolution
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raw_fallback, observed 2026-05-24T21:45:01.132006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 275cd81b-c655-4db4-bdfe-c3bf518081dc · outbound

This paper cites Convolutional Neural Networks for Sentence Classification.

Multimodal deep networks for text and image-based document classification Convolutional Neural Networks for Sentence Classification

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T21:45:01.128391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-24T21:42:20.194268Z digest=sha256:5a35cf51e52f4dcc7b091963c2370b5feaddcdfef582717a29e27b2528ab63dd

Observation 207a73e0-08df-4415-a4f4-6128d6f1b57a · outbound

This paper cites Nielsen, Usability Engineering.

Multimodal deep networks for text and image-based document classification Nielsen, Usability Engineering

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T21:45:01.106140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-24T21:42:20.194268Z digest=sha256:436e6747cdd06094e5b25995ce98ae0accd55ec37e640df9f4eba547b74da15d

Observation 91db809d-807d-499c-b5b4-8a171ee036f6 · outbound

This paper cites Xception: Deep Learning with Depthwise Separable Convolutions.

Multimodal deep networks for text and image-based document classification Xception: Deep Learning with Depthwise Separable Convolutions

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T21:45:01.038938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-24T21:42:20.194268Z digest=sha256:7a5338ea7c4ff865181581aa8109c8adbeabe7b2b58c5e4a485c73c53ab3b6e6

Observation e31bdd73-6a2d-4f65-8b4a-54b5c3399e93 · outbound

This paper cites Robust W ord V ectors: Context-Informed Embeddings for Noisy T exts.

Multimodal deep networks for text and image-based document classification Robust W ord V ectors: Context-Informed Embeddings for Noisy T exts

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T21:45:01.062052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-24T21:42:20.194268Z digest=sha256:d004fcca723682519fd66f7bb041c6e8ba0844d0c881c9c7bc53a3f53651cb35

Pith citing papers

Observation 2f14f9d6-b3d2-4ed3-bae5-e44846f08e23 · inbound

STORM: Strategic Orchestration of Modalities for Rare Event Classification cites this paper.

STORM: Strategic Orchestration of Modalities for Rare Event Classification Multimodal deep networks for text and image-based document classification

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T23:09:14.760420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:09:14.760420Z digest=sha256:f1909855804f026ac97e5b5b66009cdeccbe9232e5e80d646bc2c59928baa79f

Observation 887f58c5-5661-4ee7-aced-79028738d899 · inbound

WordVIS: A Color Worth A Thousand Words cites this paper.

WordVIS: A Color Worth A Thousand Words Multimodal deep networks for text and image-based document classification

Reference 5

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T16:21:06.403367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T16:21:06.070650Z digest=sha256:544be44086bc46ed0f5dc00a838268d4c33848270ca9563fe8c2ec22ca93c5a6