Paper Citation Record · LEDGER

Utilizing Large Language Models to Synthesize Product Desirability Datasets

As of 12 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2411.13485.

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

pith.paper-citation-record.v1
2411.13485 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:26:14.875977Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

49 of 49 outbound references displayed

verified exact11
verified fuzzy14
unresolved14
parse uncertain0
malformed identifier5
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b744cd5-69a0-4908-bcc0-738fc41f0684 · outbound

This paper cites Synthetic data generator for classification rules learning,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Synthetic data generator for classification rules learning,

Reference 1

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Observation 03818fdd-e4ec-4c3d-b816-f16f4e193396 · outbound

This paper cites Exploring large language models for low-resource IT information extraction,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Exploring large language models for low-resource IT information extraction,

Reference 2

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Source-reported events for the cited work

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Synthetic datasets generator for testing information visualization and machine learning techniques and tools,

Reference 3

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Observation 9e7b4fcb-8423-4de0-9cc8-bf8580d85d43 · outbound

This paper cites Criteria for a comparative study of visualization techniques in data mining,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Criteria for a comparative study of visualization techniques in data mining,

Reference 4

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Observation 996552cd-e004-438b-8fea-2cac51305372 · outbound

This paper cites Between level up and game over: A systematic literature review of gamification in education,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Between level up and game over: A systematic literature review of gamification in education,

Reference 5

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Source-reported events for the cited work

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Observation 5916ea72-7709-40f4-9edf-eb6ab1e5baa7 · outbound

This paper cites Generation and evaluation of synthetic patient data,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Generation and evaluation of synthetic patient data,

Reference 6

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Source-reported events for the cited work

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Observation 939cbefc-0425-43b9-8a24-f4638daa5957 · outbound

This paper cites A review of feature selection methods on synthetic data,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets A review of feature selection methods on synthetic data,

Reference 7

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Observation 1b1e4e8c-7407-4518-88c3-8283da06624b · outbound

This paper cites Data generators: A short survey of techniques and use cases with focus on testing,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Data generators: A short survey of techniques and use cases with focus on testing,

Reference 8

Resolution: verified exact; raw_fallback, observed 2026-08-12T16:26:15.926801Z

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Observation ac635624-2354-486a-bace-990a5d4c2f51 · outbound

This paper cites Development of a synthetic data set generator for building and testing information discovery systems,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Development of a synthetic data set generator for building and testing information discovery systems,

Reference 9

Resolution: verified exact; doi, observed 2026-08-12T16:26:15.048907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d7b2442e-c9a4-4d62-abe2-965d20d85735 · outbound

This paper cites Analysis of Facebook interaction as basis for synthetic expanded social graph generation,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Analysis of Facebook interaction as basis for synthetic expanded social graph generation,

Reference 10

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Source-reported events for the cited work

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Observation 631b8765-c3c8-4a06-858e-c94028dc7480 · outbound

This paper cites Generating datasets with pretrained lan- guage models,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Generating datasets with pretrained lan- guage models,

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 648584dc-cb29-46b9-b0f7-f51ef7f89835 · outbound

This paper cites Sentiment analysis in online product reviews: Mining customer opinions for sentiment classification,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Sentiment analysis in online product reviews: Mining customer opinions for sentiment classification,

Reference 12

Resolution: verified exact; doi, observed 2026-08-12T16:26:15.030910Z

Source-reported events for the cited work

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Observation 1108a2db-ca2c-4208-811b-5e72fe459787 · outbound

This paper cites Do not have enough data? Deep learning to the rescue!.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Do not have enough data? Deep learning to the rescue!

Reference 13

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Source-reported events for the cited work

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Observation 796461cb-e33e-4014-9de8-ce4fa616c957 · outbound

This paper cites Synthesize step-by-step: Tools, templates and LLMs as data generators for reasoning-based chart VQA,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Synthesize step-by-step: Tools, templates and LLMs as data generators for reasoning-based chart VQA,

Reference 14

Resolution: malformed identifier; no resolver link, observed 2026-08-12T16:26:14.742535Z

Source-reported events for the cited work

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Observation 2d381dca-8060-4d30-a435-8f61ee39dad7 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d6a9d052-f510-443a-82d9-8c696d806e13 · outbound

This paper cites Clustering to categorize desir- ability in software: Exploring cluster analysis of product reaction cards in a stereoscopic retail application,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Clustering to categorize desir- ability in software: Exploring cluster analysis of product reaction cards in a stereoscopic retail application,

Reference 16

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Source-reported events for the cited work

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Observation 8fd597c7-f21d-4195-a276-cc932b42847b · outbound

This paper cites A supporting tool for enhancing user’s mental model elicitation and decision-making in user experi- ence research,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets A supporting tool for enhancing user’s mental model elicitation and decision-making in user experi- ence research,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.210588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bb67b74b-7d88-49b8-8c4e-85e0b6391169 · outbound

This paper cites Mapping customer needs to design parameters in the front end of product design by applying deep learning,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Mapping customer needs to design parameters in the front end of product design by applying deep learning,

Reference 18

Resolution: verified exact; doi, observed 2026-08-12T16:26:15.011377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 865df3cc-f8d6-44ee-bb7c-225e4c21720d · outbound

This paper cites Analysis of sentiment expressions for user-centered design,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Analysis of sentiment expressions for user-centered design,

Reference 19

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Source-reported events for the cited work

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Observation 50955526-452b-46d9-8c00-8005cc0b8ddb · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Deep learning for sentiment analysis: A survey,

Reference 20

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Observation fd3c7f7a-cb15-4061-94b8-d4dbb41077d1 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Benedek and T

Reference 22

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Source-reported events for the cited work

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Observation 1cdbf8c6-d508-4fbe-a1d9-6d5f655e82aa · outbound

This paper cites More than a feeling: Understanding the desirability factor in user experience,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets More than a feeling: Understanding the desirability factor in user experience,

Reference 23

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Source-reported events for the cited work

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Observation aa1f852b-d2fd-4d2c-b82f-3e5490259d40 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Barnum, Usability Testing Essentials

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c9258b6e-b0c2-4547-ae97-675acbceb1bd · outbound

This paper cites End-user experiences of visual and textual programming environments for Arduino,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets End-user experiences of visual and textual programming environments for Arduino,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.190396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3b0606bf-b856-4726-abf8-cc543152da4f · outbound

This paper cites CARMA: Assessing usability through a non-biased online survey technique,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets CARMA: Assessing usability through a non-biased online survey technique,

Reference 26

Resolution: verified exact; doi, observed 2026-08-12T16:26:14.992650Z

Source-reported events for the cited work

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Observation ffbd3d0c-8a41-4af2-97a1-be6e7f60aeb1 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Mobile interface studies about style description and influential factors,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c8f1c3a0-791c-419e-abe8-6d032e2056f9 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Tullis and B

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.179908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f442d8a9-a539-4145-9d19-587a2dbccf15 · outbound

This paper cites Supporting user-perceived usability bench- marking through a developed quantitative metric,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Supporting user-perceived usability bench- marking through a developed quantitative metric,

Reference 29

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Source-reported events for the cited work

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Observation 7a70f2a4-59e2-4701-bcda-78520f69bfd7 · outbound

This paper cites Assessing user experiences with ZORQ: A gamification framework for computer science education,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Assessing user experiences with ZORQ: A gamification framework for computer science education,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.170335Z

Source-reported events for the cited work

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Observation 172cd94d-d236-4743-8a10-452c5536dda7 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Lewis and J

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.159921Z

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Observation 8a5362fd-b8fe-4055-b275-fb7fe1447caf · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Evaluation of information visualization techniques: Analysing user experience with reaction cards,

Reference 32

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Source-reported events for the cited work

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Chapter 8. capturing sensory experiences through semi-structured elicitation questions,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.149950Z

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Observation 43045788-83e0-445c-969c-c56963f7ab21 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Conceptualizing experience: A tourist based approach,

Reference 34

Resolution: verified exact; doi, observed 2026-08-12T16:26:14.974924Z

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Observation c1d741bc-0051-4b00-b702-539aecd66e09 · outbound

This paper cites Developing an instrument to capture multifaceted visitor experiences: The dove adjective checklist,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Developing an instrument to capture multifaceted visitor experiences: The dove adjective checklist,

Reference 35

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T16:26:15.295145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6d5a5c29-c0ae-469f-a5cd-10a2a4ebbb70 · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Cracking the code of mass customization,

Reference 36

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Observation fa44236b-8158-4c20-8adf-c8e8e1326142 · outbound

This paper cites Using LLMs to establish implicit user sentiment of software desirability,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Using LLMs to establish implicit user sentiment of software desirability,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.127512Z

Source-reported events for the cited work

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Observation 73a4bd3a-3216-4456-b5a8-09b1d59b6845 · outbound

This paper cites Deriving future robo-taxi ux keywords using PRC (product- reaction cards),.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Deriving future robo-taxi ux keywords using PRC (product- reaction cards),

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.117228Z

Source-reported events for the cited work

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Observation fa8266d0-f668-4182-aa3b-d7af518d30aa · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Are reference pop-up widgets welcome or annoying? a usability study,

Reference 39

Resolution: verified exact; doi, observed 2026-08-12T16:26:14.963770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8612106a-3b32-4edc-b68b-970488af0f9a · outbound

This paper cites ZORQ: A gamification framework for computer science education,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets ZORQ: A gamification framework for computer science education,

Reference 40

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This paper cites [Online].

Utilizing Large Language Models to Synthesize Product Desirability Datasets [Online]

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.106477Z

Source-reported events for the cited work

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Observation b0fd8931-6fb4-4e01-80a0-96bd6ff9f32c · outbound

This paper cites [Online].

Utilizing Large Language Models to Synthesize Product Desirability Datasets [Online]

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.096146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0b36d787-6fd9-4e20-b96a-e92396269508 · outbound

This paper cites Shaib, J.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Shaib, J

Reference 43

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Source-reported events for the cited work

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Observation 81c3f65e-9f49-4ee5-bb8e-dd357378cf0d · outbound

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Utilizing Large Language Models to Synthesize Product Desirability Datasets Hastings, S

Reference 44

Resolution: verified exact; doi, observed 2026-08-12T16:26:14.952335Z

Source-reported events for the cited work

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Observation 10b939e7-973b-4802-aeee-f238f01543cf · outbound

This paper cites [Online].

Utilizing Large Language Models to Synthesize Product Desirability Datasets [Online]

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:26:16.085164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0187b6de-ec43-454f-b9cf-0fd351f6e5d0 · outbound

This paper cites Energy and policy con- siderations for deep learning in NLP,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Energy and policy con- siderations for deep learning in NLP,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T16:26:14.860553Z

Source-reported events for the cited work

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Observation 76ab64d6-559b-499d-b17c-686a862431d4 · outbound

This paper cites Green AI,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Green AI,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T16:26:14.865890Z

Source-reported events for the cited work

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Observation 3607b747-66ff-4acd-bb39-62f2aa8d9580 · outbound

This paper cites Aligning artificial intelligence with climate change mitigation,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Aligning artificial intelligence with climate change mitigation,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T16:26:14.869438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7622acfd-743a-4f09-b45f-12f405daf754 · outbound

This paper cites Generative AI’s environmental costs are soaring — and mostly secret,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets Generative AI’s environmental costs are soaring — and mostly secret,

Reference 49

Resolution: malformed identifier; no resolver link, observed 2026-08-12T16:26:14.872680Z

Source-reported events for the cited work

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Observation 472420df-d81a-483c-8ff4-2dd74c4caa2a · outbound

This paper cites CARMA: A case-based rangeland management adviser,.

Utilizing Large Language Models to Synthesize Product Desirability Datasets CARMA: A case-based rangeland management adviser,

Reference 50

Resolution: verified exact; doi, observed 2026-08-12T16:26:14.912849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.