A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models | Paper Citation Record

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This paper cites Cataloging and classification: an introduction.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Cataloging and classification: an introduction

Reference 1

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This paper cites Machine learning in automated text categorization.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Machine learning in automated text categorization

Reference 2

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This paper cites Automated knowledge organisation: Ai/ml-based subject indexing system for libraries.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Automated knowledge organisation: Ai/ml-based subject indexing system for libraries

Reference 3

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This paper cites Automatically cataloging scholarly articles using library of congress subject headings.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Automatically cataloging scholarly articles using library of congress subject headings

Reference 4

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This paper cites Hierarchical multi-label classification networks.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Hierarchical multi-label classification networks

Reference 5

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This paper cites A review of methods for imbalanced multi-label classification.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models A review of methods for imbalanced multi-label classification

Reference 6

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This paper cites An experiment with the use of chatgpt for lcsh subject assignment on electronic theses and dissertations.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models An experiment with the use of chatgpt for lcsh subject assignment on electronic theses and dissertations

Reference 7

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This paper cites Few-shot prompting for subject indexing of german medical book titles.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Few-shot prompting for subject indexing of german medical book titles

Reference 8

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This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

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This paper cites Fine-tuning large language models for scientific text classification: A comparative study.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Fine-tuning large language models for scientific text classification: A comparative study

Reference 10

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This paper cites A performance model of the length and number of subject headings and index phrases.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models A performance model of the length and number of subject headings and index phrases

Reference 11

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This paper cites Artificial intelligence (ai) library services innovative conceptual framework for the digital transformation of university education.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Artificial intelligence (ai) library services innovative conceptual framework for the digital transformation of university education

Reference 12

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This paper cites Defining artificial intelligence for librarians.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Defining artificial intelligence for librarians

Reference 13

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models A survey of knowledge-enhanced text generation

Reference 14

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This paper cites Machine learning and ontology-based novel semantic document indexing for information retrieval.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Machine learning and ontology-based novel semantic document indexing for information retrieval

Reference 15

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This paper cites Hdltex: Hierarchical deep learning for text classification.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Hdltex: Hierarchical deep learning for text classification

Reference 16

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This paper cites Large scale subject category classification of scholarly papers with deep attentive neural networks.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Large scale subject category classification of scholarly papers with deep attentive neural networks

Reference 17

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This paper cites A survey of controllable text generation using transformer-based pre-trained language models.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models A survey of controllable text generation using transformer-based pre-trained language models

Reference 18

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This paper cites An integrated clustering and bert framework for improved topic modeling.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models An integrated clustering and bert framework for improved topic modeling

Reference 19

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This paper cites A survey of multi-label classification based on supervised and semi-supervised learning.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models A survey of multi-label classification based on supervised and semi-supervised learning

Reference 20

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This paper cites Advancing automatic subject indexing: Combining weak supervision with extreme multi-label classification.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Advancing automatic subject indexing: Combining weak supervision with extreme multi-label classification

Reference 21

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Artificial intelligence chatbots in academic libraries: the rise of chatgpt

Reference 22

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Data-efficient fine-tuning for llm-based recommendation

Reference 23

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Comparative Study of Domain Driven Terms Extraction Using Large Language Models

Reference 24

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Llm-take: Theme-aware keyword extraction using large language models

Reference 25

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This paper cites Utilising a Large Language Model to Annotate Subject Metadata: A Case Study in an Australian National Research Data Catalogue.

A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Utilising a Large Language Model to Annotate Subject Metadata: A Case Study in an Australian National Research Data Catalogue

Reference 26

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Structured information extraction from complex scientific text with fine-tuned large language models

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Gpt4roi: Instruction tuning large language model on region-of-interest

Reference 28

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Training language models to follow instructions with human feedback

Reference 29

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Lora: Low-rank adaptation of large language models

Reference 30

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Discover: The unt library catalog, n.d

Reference 31

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models The Llama 3 Herd of Models

Reference 32

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models GPT-4 Technical Report

Reference 33

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models DeepSeek-V3 Technical Report

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Qwen3 Technical Report

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 36

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 37

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models SciBERT: A Pretrained Language Model for Scientific Text

Reference 38

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Transformer in transformer

Reference 39

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Transformer models: an introduction and catalog

Reference 40

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Reference 41

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Random forests

Reference 42

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Linear regression

Reference 43

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Xgboost: A scalable tree boosting system

Reference 44

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Analysis of a complex of statistical variables into principal components

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models Approximate nearest neighbor search in high dimensions

Reference 46

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A Hybrid Framework for Subject Analysis: Integrating Embedding-Based Regression Models with Large Language Models The Faiss library

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