Paper Citation Record · LEDGER

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction

As of 7 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2505.21109.

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

pith.paper-citation-record.v1
2505.21109 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

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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.

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Reference resolution

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External citation measurements

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Outbound references

Observation 23a5d96a-75c8-4e11-8519-6fca093876aa · outbound

This paper cites “OpenAI.” https://openai.com.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction “OpenAI.” https://openai.com

Reference 1

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This paper cites “Gemini.” https://gemini.google.com/app.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction “Gemini.” https://gemini.google.com/app

Reference 2

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Observation 1c06685d-f9fc-49eb-bcf6-ac8baca2b820 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction LLaMA: Open and Efficient Foundation Language Models

Reference 3

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This paper cites From Language Models to Practical Self-Improving Computer Agents.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction From Language Models to Practical Self-Improving Computer Agents

Reference 4

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 5

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction ReAct — Synergizing Reasoning and Acting in Language Models

Reference 6

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Data-driven innovation: What is it?

Reference 7

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This paper cites A data-driven approach for creative concept gener- ation and evaluation.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction A data-driven approach for creative concept gener- ation and evaluation

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction EW-Tune: A FrameworkforPrivatelyFine-TuningLargeLanguageMod- els with Differential Privacy

Reference 9

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This paper cites Exploring the limits of transfer learning withaunifiedtext-to-texttransformer.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Exploring the limits of transfer learning withaunifiedtext-to-texttransformer

Reference 10

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Observation 259d55dd-0b9d-4125-a906-b8a96651a5c2 · outbound

This paper cites Languagemodelsare unsupervisedmultitasklearners.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Languagemodelsare unsupervisedmultitasklearners

Reference 11

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction AttentionisAllyouNeed

Reference 12

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction meta-llama/Llama-3.2-1B-Instruct

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction The Llama 3 Herd of Models

Reference 14

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Observation ec8b88e4-4b2e-48a0-ab07-e377e4d93918 · outbound

This paper cites Causal Parrots: Large Lan- guage Models May Talk Causality But Are Not Causal.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Causal Parrots: Large Lan- guage Models May Talk Causality But Are Not Causal

Reference 15

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Observation a8a1f837-03ac-4926-b388-f8d42cbd9462 · outbound

This paper cites Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models

Reference 16

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This paper cites Conceptual Design Generation Using Large Language Mod- els.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Conceptual Design Generation Using Large Language Mod- els

Reference 17

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Augmenting human innovation teams with arti- ficial intelligence: Exploring transformer-based language models

Reference 18

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This paper cites Artificial intelligence prompt engineering as a new digital competence: Anal- ysis of generative AI technologies such as ChatGPT.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Artificial intelligence prompt engineering as a new digital competence: Anal- ysis of generative AI technologies such as ChatGPT

Reference 19

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

Reference 20

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Finetuned Language Models Are Zero-Shot Learners

Reference 21

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Observation d94bb597-0046-4af5-81ca-07cc1ad6f6f9 · outbound

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction LaMDA: Language Models for Dialog Applications

Reference 22

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Efficient Hierarchical Domain Adaptation for Pretrained Language Models

Reference 23

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Observation 7ac8ef22-f9a9-450c-92e2-46e1d968fa94 · outbound

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction LoRA: Low-Rank Adaptation of Large Language Models

Reference 24

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 25

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Enhancing Retrieval-Augmented Generation: AStudyofBestPractices

Reference 26

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This paper cites Im- proving large language model applications in biomedicine with retrieval-augmented generation: a systematic re- view, meta-analysis, and clinical development guide- lines.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Im- proving large language model applications in biomedicine with retrieval-augmented generation: a systematic re- view, meta-analysis, and clinical development guide- lines

Reference 27

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Question-Based Retrieval using Atomic Units for Enterprise RAG

Reference 28

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 29

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This paper cites In- formation Extraction of Aviation Accident Causation Knowledge Graph: An LLM-Based Approach.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction In- formation Extraction of Aviation Accident Causation Knowledge Graph: An LLM-Based Approach

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction MechBERT: Language Models for Extracting Chemical 9 and Property Relationships about Mechanical Stress and Strain

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction An Approach to Intelligent Information Extraction and Utilization from Diverse Documents

Reference 32

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This paper cites Single Engine Models 172, 182, T182, 206 AND T206 1996 And On.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction Single Engine Models 172, 182, T182, 206 AND T206 1996 And On

Reference 33

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction meta-llama/Llama-3.3-70B-Instruct

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction LangGraph

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction meta-llama/Llama-3.1-8B-Instruct

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction fine-tune: full fine-tuning pipeline

Reference 37

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction “Llama.” https://www.llama.com/

Reference 38

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This paper cites The Bittorrent P2P File-Sharing System: Mea- surements and Analysis.

A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction The Bittorrent P2P File-Sharing System: Mea- surements and Analysis

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A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction URL https://www.scopus.com/inward/record

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Pith citing papers

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