Paper Citation Record · LEDGER

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents

As of 14 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2501.05082.

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

pith.paper-citation-record.v1
2501.05082 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:25:37.637085Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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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

42 of 42 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 56ef4e5e-691a-4d61-82ce-4789cd6f9ce0 · outbound

This paper cites Openaire research graph dump,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Openaire research graph dump,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.654489Z

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Observation eae3f38f-b1cf-41a9-b620-abd99d849474 · outbound

This paper cites Open research knowledge graph: next generation infrastructure for semantic scholarly knowledge,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Open research knowledge graph: next generation infrastructure for semantic scholarly knowledge,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.637329Z

Source-reported events for the cited work

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Observation ceb212ee-36f8-4361-ab49-c15a7b69ee20 · outbound

This paper cites Mexpub: Deep transfer learning for metadata extraction from german publications,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Mexpub: Deep transfer learning for metadata extraction from german publications,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.618161Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 16827063-ddda-4086-8828-e9456436b21f · outbound

This paper cites Vision and natural language for meta- data extraction from scientific pdf documents: a multimodal approach,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Vision and natural language for meta- data extraction from scientific pdf documents: a multimodal approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.598926Z

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Observation 9df910c5-afb6-4b8b-a645-9b8b946a97dd · outbound

This paper cites Clinical information extrac- tion applications: a literature review,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Clinical information extrac- tion applications: a literature review,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.580131Z

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Observation 248dc29c-1016-4dec-adc5-13bfbc97a53d · outbound

This paper cites Advances in natural language processing,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Advances in natural language processing,

Reference 6

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Source-reported events for the cited work

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Observation 3328144b-c5de-4f65-a433-8f62f3a4e174 · outbound

This paper cites An efficient framework for metadata extraction over scholarly documents using ensemble cnn and bilstm technique,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents An efficient framework for metadata extraction over scholarly documents using ensemble cnn and bilstm technique,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.545233Z

Source-reported events for the cited work

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Observation a0782bf0-094e-4473-bcd4-df4693c2b9bf · outbound

This paper cites Computer vision and machine learning approaches for metadata enrichment to improve searchability of historical newspaper collections,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Computer vision and machine learning approaches for metadata enrichment to improve searchability of historical newspaper collections,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.530423Z

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Observation 8b8982a6-d296-4f8d-ae47-2d14eedc0b81 · outbound

This paper cites A multimodal approach for extracting content descriptive metadata from lecture videos,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents A multimodal approach for extracting content descriptive metadata from lecture videos,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.515661Z

Source-reported events for the cited work

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Observation e35bb7f8-2738-46ee-adb0-3628bedb69ce · outbound

This paper cites Reference metadata extraction using a hierarchical knowledge representation framework,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Reference metadata extraction using a hierarchical knowledge representation framework,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.496991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c148cd90-8722-479e-bc2a-8e1f2093b47e · outbound

This paper cites A unified framework for automatic metadata extraction from electronic document,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents A unified framework for automatic metadata extraction from electronic document,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.481232Z

Source-reported events for the cited work

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Observation 8d73c440-a5d0-42cf-ba97-5ccf0487e769 · outbound

This paper cites Rule-based word clustering for document metadata extraction,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Rule-based word clustering for document metadata extraction,

Reference 12

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Source-reported events for the cited work

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Observation 6e959dc2-5b8f-4df5-814a-33f0d89559cf · outbound

This paper cites Citeseerx: an architecture and web service design for an academic document search engine,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Citeseerx: an architecture and web service design for an academic document search engine,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.464612Z

Source-reported events for the cited work

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Observation 995ce91a-12e9-4789-a8df-834f0561babe · outbound

This paper cites Learning hidden markov model structure for information extraction,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Learning hidden markov model structure for information extraction,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.448555Z

Source-reported events for the cited work

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Observation 76cfc604-1111-480d-9195-f4f06486bc70 · outbound

This paper cites Information extraction from research papers using conditional random fields,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Information extraction from research papers using conditional random fields,

Reference 15

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Observation 63c8bd9e-3131-4906-ac04-66dd94c2b69e · outbound

This paper cites Auto- matic document metadata extraction using support vector machines,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Auto- matic document metadata extraction using support vector machines,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.431805Z

Source-reported events for the cited work

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Observation 94ff1783-893d-4e89-9cb0-732c62a0c9fa · outbound

This paper cites Bidirectional LSTM-CRF Models for Sequence Tagging.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Bidirectional LSTM-CRF Models for Sequence Tagging

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T21:25:37.493973Z

Source-reported events for the cited work

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Observation 4ef59b07-9a44-4db4-839b-210fd4441225 · outbound

This paper cites Named Entity Recognition with Bidirectional LSTM-CNNs.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Named Entity Recognition with Bidirectional LSTM-CNNs

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T21:25:37.500564Z

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Observation 23ac7c73-1eb0-43a3-9457-d7c926b90f92 · outbound

This paper cites Citation metadata extraction via deep neural network-based segment sequence labeling,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Citation metadata extraction via deep neural network-based segment sequence labeling,

Reference 19

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Observation 84717d25-cd2a-476f-b2fc-2030e49a263c · outbound

This paper cites Parscit: an open-source crf reference string parsing package,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Parscit: an open-source crf reference string parsing package,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.416047Z

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Observation 78360d4a-5907-4a00-917c-8a2e35a91772 · outbound

This paper cites Bibpro: A citation parser based on sequence alignment,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Bibpro: A citation parser based on sequence alignment,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.399153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3276a74f-f045-4e4a-a1f3-fd58a9f67874 · outbound

This paper cites A new dataset for fine-grained citation field extraction,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents A new dataset for fine-grained citation field extraction,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.382246Z

Source-reported events for the cited work

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Observation 3f353a66-909f-4681-9934-c381bb228587 · outbound

This paper cites Deeppdf: A deep learning approach to extracting text from pdfs,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Deeppdf: A deep learning approach to extracting text from pdfs,

Reference 23

Resolution: verified exact; raw_fallback, observed 2026-08-10T21:25:37.891496Z

Source-reported events for the cited work

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Observation dffdefcf-c4f2-4b99-a91f-7724b4955f14 · outbound

This paper cites Mexpub: Deep transfer learning for metadata extraction from german publications,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Mexpub: Deep transfer learning for metadata extraction from german publications,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.363944Z

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Observation a9025084-2a8a-4fac-9b22-45f2e298c9db · outbound

This paper cites Mask r-cnn,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Mask r-cnn,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.346155Z

Source-reported events for the cited work

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Observation eea85de3-10b7-43a3-bf75-b0a03127309a · outbound

This paper cites Aggregated Residual Transformations for Deep Neural Networks.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Aggregated Residual Transformations for Deep Neural Networks

Reference 26

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Observation 112d1166-7944-4858-b23a-1284b78e1e15 · outbound

This paper cites A multimodal approach for extracting content descriptive metadata from 14 lecture videos,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents A multimodal approach for extracting content descriptive metadata from 14 lecture videos,

Reference 27

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Observation 2320764d-c9fe-48ff-81b2-a0bea686f20f · outbound

This paper cites Automatic document metadata extraction based on deep networks,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Automatic document metadata extraction based on deep networks,

Reference 28

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Observation 1b350f87-a2b9-4a79-897e-248b920028d2 · outbound

This paper cites Arctic: metadata extraction from scientific papers in pdf using two-layer crf,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Arctic: metadata extraction from scientific papers in pdf using two-layer crf,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.312076Z

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Observation e32c1f7e-5121-455b-999b-83a6e2b850ea · outbound

This paper cites Bi-lstm-crf sequence labeling for keyphrase extraction from scholarly documents,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Bi-lstm-crf sequence labeling for keyphrase extraction from scholarly documents,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.294799Z

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Observation d9b2fed9-7fcf-44cb-97ce-ef0f0c86eb90 · outbound

This paper cites Grantex- tractor: Accurate grant support information extraction from biomedical fulltext based on bi-lstm-crf,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Grantex- tractor: Accurate grant support information extraction from biomedical fulltext based on bi-lstm-crf,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.277169Z

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Observation 9bd37fff-3aa5-43ba-8320-18359b91053c · outbound

This paper cites Mask r-cnn,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Mask r-cnn,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T21:25:37.579124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76f28194-044a-4e3c-a6f8-7063490d8ff1 · outbound

This paper cites Aggregated residual transformations for deep neural networks,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Aggregated residual transformations for deep neural networks,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T21:25:37.584288Z

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Observation 1db4b975-638f-4cd4-9242-84bb2a6ba342 · outbound

This paper cites Feature pyramid networks for object detection,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Feature pyramid networks for object detection,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T21:25:37.590136Z

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Observation 0a4308df-41b9-41ac-ae84-daf59f5073b8 · outbound

This paper cites A survey on transfer learning,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents A survey on transfer learning,

Reference 36

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This paper cites Detectron2,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Detectron2,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T21:25:37.600686Z

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Observation d8b61b38-b793-4d73-9275-c789f114e692 · outbound

This paper cites Publaynet: largest dataset ever for document layout analysis,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Publaynet: largest dataset ever for document layout analysis,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.201378Z

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Observation 81fd5d5c-9808-454c-8aef-aa99d859996e · outbound

This paper cites Cermine: Automatic extraction of structured metadata from scientific literature,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Cermine: Automatic extraction of structured metadata from scientific literature,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.183094Z

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Observation 45e0f3e2-d4cc-45f6-b9ec-ca6103048b8b · outbound

This paper cites Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:25:37.752359Z

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Observation 49e60af0-5d34-4063-8eb5-a23d7f739515 · outbound

This paper cites S2ORC: The Semantic Scholar Open Research Corpus.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents S2ORC: The Semantic Scholar Open Research Corpus

Reference 41

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This paper cites Crossref: The sus- tainable source of community-owned scholarly metadata,.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Crossref: The sus- tainable source of community-owned scholarly metadata,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:25:38.163371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0cc1bdda-a843-46fe-af39-66504bc61563 · outbound

This paper cites Available: https://doi.org/10.1007/s10032-015-0249-8.

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Available: https://doi.org/10.1007/s10032-015-0249-8

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T21:25:37.620960Z

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Pith citing papers

No inbound Pith citation observations are available.