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Paper Citation Record · LEDGER

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2505.17634.

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

pith.paper-citation-record.v1
2505.17634 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:46:00.744358Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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 exact1
  • verified fuzzy30
  • unresolved1
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c17a1fc8-11c0-437d-9a36-d949b8e2e7cb · outbound

This paper cites Impact of word embedding models on text analytics in deep learning environment: a review.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Impact of word embedding models on text analytics in deep learning environment: a review

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c0be63f1-431b-4aec-85ee-847d565ec7f8 · outbound

This paper cites An empirical study on the potential of word embedding techniques in bug report management tasks.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain An empirical study on the potential of word embedding techniques in bug report management tasks

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:06.530854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d346712f-ec78-4a96-aaa9-db327de71e4c · outbound

This paper cites Linguistic regularities in continuous space word representations.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Linguistic regularities in continuous space word representations

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:06.370160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1e37fd0e-bee5-4536-97bf-30a37cbb72a6 · outbound

This paper cites A review on word embedding techniques for text classification.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain A review on word embedding techniques for text classification

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:06.154553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5b4e4e8c-1ca5-422f-9a97-7b7d36c6309f · outbound

This paper cites Deep learning with word embeddings improves biomedical named entity recognition.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Deep learning with word embeddings improves biomedical named entity recognition

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.963532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 73629352-b72e-4e47-a6a1-0f1a0e0b7b60 · outbound

This paper cites Learning continuous word embedding with metadata for question retrieval in community question answering.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Learning continuous word embedding with metadata for question retrieval in community question answering

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.779641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7ca61d71-e943-49dd-acae-8fdb77e4e43a · outbound

This paper cites Deep contextualized Word representations.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Deep contextualized Word representations

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.593001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5af25663-b6c3-459c-bc80-01a323c2316a · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understand- ing.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Bert: Pre-training of deep bidirectional transformers for language understand- ing

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.433801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 546ef1b0-9ea5-4783-b8dd-ef07ea948814 · outbound

This paper cites Software development methods: Review and outlook.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Software development methods: Review and outlook

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.267367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 708e6570-6b5d-46cf-a122-e7e44f973ffc · outbound

This paper cites FineLocator: A novel approach to method-level fine-grained bug localization by query expansion.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain FineLocator: A novel approach to method-level fine-grained bug localization by query expansion

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.040817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a019e0e9-a7c8-45de-a8e6-08ed7c05bba9 · outbound

This paper cites Fast changeset-based bug localization with BERT.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Fast changeset-based bug localization with BERT

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3532c217-f41e-407e-8515-1839de134c34 · outbound

This paper cites Automatic text input generation for mobile testing.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Automatic text input generation for mobile testing

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.695472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 68589c2b-4550-4dd2-89c4-32d01ee02539 · outbound

This paper cites Apiro: A framework for automated security tools api recommendation.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Apiro: A framework for automated security tools api recommendation

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9ecc886c-cac4-4bf6-9640-4a2aacb5bdf3 · outbound

This paper cites Mining user opinions in mobile app reviews: A keyword-based approach (t).

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Mining user opinions in mobile app reviews: A keyword-based approach (t)

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.282028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 886d20c7-277c-4678-8483-3e46ba8e2786 · outbound

This paper cites Efficient estimation of word representations in vector space.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Efficient estimation of word representations in vector space

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.112909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9519344e-3b84-4c10-9e5b-ee4cb5927808 · outbound

This paper cites Glove: Global vectors for word representation.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Glove: Global vectors for word representation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:03.915644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fc791fd0-f69a-4f3f-84db-44cb667e2785 · outbound

This paper cites Bag of tricks for efficient text classification.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Bag of tricks for efficient text classification

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 80033c62-569d-4827-8daa-07249e5560a0 · outbound

This paper cites Grounded theory research: Procedures, canons, and evaluative criteria.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Grounded theory research: Procedures, canons, and evaluative criteria

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:03.425439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ab5aa3bf-845d-4832-99c9-9f9375cd2130 · outbound

This paper cites Machine learning for software engineering: A tertiary study.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Machine learning for software engineering: A tertiary study

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:03.211183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b6c5173d-786c-430c-ad96-a6224ed40bd7 · outbound

This paper cites A survey on deep learning for software engineering.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain A survey on deep learning for software engineering

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:02.982774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6ed627d7-d79c-4207-b9b9-033ac802bfa4 · outbound

This paper cites Trends in software engineering processes using deep learning: a systematic literature review.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Trends in software engineering processes using deep learning: a systematic literature review

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 011f0412-2993-4f62-b144-8d03bb100de3 · outbound

This paper cites Machine/deep learning for software engineering: A systematic literature review.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Machine/deep learning for software engineering: A systematic literature review

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:02.642159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 024347ab-f9a1-48f7-9775-dc1269507ec0 · outbound

This paper cites Large Language Models for Software Engineering: A Systematic Literature Review.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Large Language Models for Software Engineering: A Systematic Literature Review

Reference 23

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bb9c2000-17c9-4b74-8691-fe01ac812b8f · outbound

This paper cites Text classification using embeddings: a survey.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Text classification using embeddings: a survey

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:02.494954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 34a953f4-508a-43fa-8809-70eb61ba57b5 · outbound

This paper cites A review on word embedding techniques for text classification.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain A review on word embedding techniques for text classification

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:02.358090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation be069a98-ccfb-49fc-a370-a516018700eb · outbound

This paper cites A systematic literature review on word embeddings.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain A systematic literature review on word embeddings

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:02.192003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 499837c5-bb5b-4655-a751-06c67f4cbfa5 · outbound

This paper cites A detailed review on word embedding techniques with emphasis on word2vec.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain A detailed review on word embedding techniques with emphasis on word2vec

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:01.978973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation af5e0a8c-a108-4145-b576-24b93c36f242 · outbound

This paper cites From word to sense embeddings: A survey on vector representations of meaning.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain From word to sense embeddings: A survey on vector representations of meaning

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:01.748567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8517b51d-0887-4756-a6ff-9ba2f00fbc9c · outbound

This paper cites A comprehensive survey on aspect based word embedding models and sentiment analysis classification approaches.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain A comprehensive survey on aspect based word embedding models and sentiment analysis classification approaches

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:01.505863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 967d70df-71c2-425f-b2b1-4575af6b95f3 · outbound

This paper cites Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:46:00.963862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c66ae3fe-9daf-4cbd-97f3-82ccebae4b9c · outbound

This paper cites A survey of cross-lingual word embedding models.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain A survey of cross-lingual word embedding models

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:01.259308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a25f5990-319b-4cd0-837e-b8dc79a75105 · outbound

This paper cites Beyond word embeddings: A survey.

A Comprehensive Study on the Use of Word Embedding Models in Software Engineering Domain Beyond word embeddings: A survey

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:01.095689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.