Paper Citation Record · LEDGER

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components

As of 20 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2505.01627.

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

pith.paper-citation-record.v1
2505.01627 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:19:22.800034Z

measured 33 of 33 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

33 of 33 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b3d93187-be33-424b-ae74-1e9eff789f2b · outbound

This paper cites Baxter,Product Design, CRC Press, 2018.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Baxter,Product Design, CRC Press, 2018

Reference 1

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Observation 7106ac96-be71-4410-aa36-efd7f0d137c8 · outbound

This paper cites Digital twin driven smart product design framework,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Digital twin driven smart product design framework,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:24.896200Z

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Observation 33483ec9-e51d-4c66-9e83-aafaacbd0903 · outbound

This paper cites An approach to identify the factors that affect a product’s life time energy consumption during the concept design stage,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components An approach to identify the factors that affect a product’s life time energy consumption during the concept design stage,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:24.828072Z

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A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Digital twin driven conceptual design,

Reference 4

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Observation fe5dbfd8-d30f-4ed6-8159-2f913fe808f6 · outbound

This paper cites Current research in the con- ceptual design of mechanical products,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Current research in the con- ceptual design of mechanical products,

Reference 5

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Observation 69113b53-90e6-4718-9e2d-8eceb94813da · outbound

This paper cites Function-behavior-structure model of de- sign: An alternative approach,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Function-behavior-structure model of de- sign: An alternative approach,

Reference 6

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Observation 131fb9e5-0673-4dd8-8922-7edd1438fa66 · outbound

This paper cites Classi- fyingcomponentfunctioninproductassemblieswithgraph neural networks,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Classi- fyingcomponentfunctioninproductassemblieswithgraph neural networks,

Reference 7

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This paper cites A functional basis for engineering design: reconciling and evolving previous efforts,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components A functional basis for engineering design: reconciling and evolving previous efforts,

Reference 8

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This paper cites A review on large language models: Architectures, ap- plications, taxonomies, open issues and challenges,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components A review on large language models: Architectures, ap- plications, taxonomies, open issues and challenges,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:24.403718Z

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This paper cites ChatGPT: A comprehensive review on back- ground, applications, key challenges, bias, ethics, limi- tations and future scope,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components ChatGPT: A comprehensive review on back- ground, applications, key challenges, bias, ethics, limi- tations and future scope,

Reference 10

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Observation aa04519e-da7a-4462-a4af-2deac9471502 · outbound

This paper cites Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 11

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Observation 524e1668-ddcb-47d1-85df-ef97d1487c57 · outbound

This paper cites Classifyingfunctionsfor mechanical design,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Classifyingfunctionsfor mechanical design,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:24.307120Z

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Observation bbe76124-7094-4d82-83b1-3b23582a9165 · outbound

This paper cites Automatic annotation of functional semantics for 3D product model based on latent functional semantics,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Automatic annotation of functional semantics for 3D product model based on latent functional semantics,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:24.249881Z

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Observation e46a30ab-ec02-43ed-a6c8-8d296615bfe5 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components A Comprehensive Overview of Large Language Models

Reference 14

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Observation 7cbfc7ff-955b-425c-af38-9ef7280751aa · outbound

This paper cites Transform- ers: ‘Theendofhistory’fornaturallanguageprocessing?,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Transform- ers: ‘Theendofhistory’fornaturallanguageprocessing?,

Reference 15

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Observation 88b7698a-13f3-402f-b5c8-6101b426dcd2 · outbound

This paper cites A survey on large language models: Applications, challenges, lim- itations, and practical usage,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components A survey on large language models: Applications, challenges, lim- itations, and practical usage,

Reference 16

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Observation d275c569-5e4a-4371-b740-c4a2dd561ab9 · outbound

This paper cites AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset

Reference 17

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Observation a1866a4a-f6b3-47cb-bebb-de9fb10d23b4 · outbound

This paper cites Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine

Reference 18

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A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Unresolved cited work

Reference 19

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Observation e4526cb0-f907-4f74-813a-df76afd1a661 · outbound

This paper cites LLM4CAD: Multi-modal large languagemodelsfor3Dcomputer-aideddesigngeneration,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components LLM4CAD: Multi-modal large languagemodelsfor3Dcomputer-aideddesigngeneration,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:24.054899Z

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Observation 53b40082-2569-4d66-8579-7334fe86e0ac · outbound

This paper cites Elicitron: A large language model agent-based simulation framework for design requirements elicitation,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Elicitron: A large language model agent-based simulation framework for design requirements elicitation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:24.015658Z

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Observation 53cabbe7-ece7-4852-946b-a7a3e587f044 · outbound

This paper cites Monitoring blockchain cryp- tocurrency transactions to improve the trustworthiness of the fourth industrial revolution (Industry 4.0),.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Monitoring blockchain cryp- tocurrency transactions to improve the trustworthiness of the fourth industrial revolution (Industry 4.0),

Reference 22

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Observation 3cfc32f8-e8a5-4706-909d-99cf008d8a6e · outbound

This paper cites Developing a method for modeling and monitoring of dynamic networks using latent variables,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Developing a method for modeling and monitoring of dynamic networks using latent variables,

Reference 23

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This paper cites A latentspacemodelandHotelling’sT 2controlcharttomoni- torthenetworksofCovid-19symptoms,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components A latentspacemodelandHotelling’sT 2controlcharttomoni- torthenetworksofCovid-19symptoms,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:23.876501Z

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Observation e22980d6-e78c-4c7b-9d20-7d545f67b83d · outbound

This paper cites TheSCANmethod to monitor cryptocurrency transactions,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components TheSCANmethod to monitor cryptocurrency transactions,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:23.814436Z

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This paper cites The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities

Reference 26

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Observation 180fc795-3304-4d34-9857-4cc77e9a6586 · outbound

This paper cites Supervised domain adaptation by transferring both the parameter set and its gradient,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Supervised domain adaptation by transferring both the parameter set and its gradient,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:23.745331Z

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Observation b20ff88a-2d83-4065-8d81-fe9352c01452 · outbound

This paper cites Development of a functional basisfordesign,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Development of a functional basisfordesign,

Reference 28

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Observation 0576fd1c-d643-471b-bb45-ffea8a492cec · outbound

This paper cites Attention is all you need,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Attention is all you need,

Reference 29

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This paper cites Integrating graph retrieval- augmented generation with large language models for sup- plier discovery,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Integrating graph retrieval- augmented generation with large language models for sup- plier discovery,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:23.578115Z

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Observation 80c75079-4d3a-4065-b370-b0744fc0f80d · outbound

This paper cites Introduction of a data schema to support a design reposi- tory,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Introduction of a data schema to support a design reposi- tory,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:23.508072Z

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Observation 3127addc-84d6-4224-ad33-5524ec395e2f · outbound

This paper cites Product design support: Exploringadesignrepositorysystem,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components Product design support: Exploringadesignrepositorysystem,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:23.479543Z

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Observation bbcc0b62-5349-49d3-8eda-0cca4fba2e59 · outbound

This paper cites ABC: A big CAD model dataset for geometric deep learning,.

A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components ABC: A big CAD model dataset for geometric deep learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:19:23.412395Z

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.

Pith citing papers

No inbound Pith citation observations are available.