A comparative analysis of knowledge injection strategies for large language models in the scholarly domain-Reference-Cited by-同舟云学术

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A comparative analysis of knowledge injection strategies for large language models in the scholarly domain

Published:2024-07 Issue: Volume:133 Page:108166
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Cadeddu Andrea,Chessa Alessandro,De Leo Vincenzo^ORCID,Fenu Gianni^ORCID,Motta Enrico,Osborne Francesco^ORCID,Reforgiato Recupero Diego^ORCID,Salatino Angelo,Secchi Luca^ORCID

Publisher

Elsevier BV

Reference75 articles.

1. R-classify: Extracting research papers’ relevant concepts from a controlled vocabulary;Aggarwal;Softw. Impacts,2022

2. Named entity extraction for knowledge graphs: A literature overview;Al-Moslmi;IEEE Access,2020

3. Artificial hallucinations in ChatGPT: implications in scientific writing;Alkaissi;Cureus,2023

4. Neuro-symbolic visual reasoning: Disentangling “visual” from “reasoning”;Amizadeh,2020

5. The AIDA dashboard: Analysing conferences with semantic technologies;Angioni,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies;Information;2024-07-10

2. Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark;Lecture Notes in Computer Science;2024

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