期刊名：Machine Learning and Knowledge Extraction

期刊主页：https://www.mdpi.com/journal/make

大语言模型Large Language Models (LLMs)还能怎么玩？提示工程、RAG、知识图谱、医疗问答、教育应用……15篇精选论文，带你一次看够LLMs的前沿探索！

1. Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language Models

提示工程还是微调？以大语言模型进行网络钓鱼检测的案例研究

http://www.mdpi.com/2504-4990/6/1/18

Trad, F.; Chehab, A. Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language Models. Mach. Learn. Knowl. Extr. 2024, 6, 367-384.

2. Enhancing Legal Sentiment Analysis: A Convolutional Neural Network–Long Short-Term Memory Document-Level Model

增强法律情感分析：基于CNN-LSTM的文档级模型

http://www.mdpi.com/2504-4990/6/2/41

Abimbola, B.; de La Cal Marin, E.; Tan, Q. Enhancing Legal Sentiment Analysis: A Convolutional Neural Network–Long Short-Term Memory Document-Level Model. Mach. Learn. Knowl. Extr. 2024, 6, 877-897.

3. Image Text Extraction and Natural Language Processing of Unstructured Data from Medical Reports

医学报告中非结构化数据的图像文本提取与自然语言处理

http://www.mdpi.com/2504-4990/6/2/64

Malashin, I.; Masich, I.; Tynchenko, V.; Gantimurov, A.; Nelyub, V.; Borodulin, A. Image Text Extraction and Natural Language Processing of Unstructured Data from Medical Reports. Mach. Learn. Knowl. Extr. 2024, 6, 1361-1377.

4. A Study on Text Classification in the Age of Large Language Models

大语言模型时代的文本分类研究

http://www.mdpi.com/2504-4990/6/4/129

Trust, P.; Minghim, R. A Study on Text Classification in the Age of Large Language Models. Mach. Learn. Knowl. Extr. 2024, 6, 2688-2721.

5. Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes

利用大语言模型优化食谱中的成分替代以增强植物化学物质含量

http://www.mdpi.com/2504-4990/6/4/131

Rita, L.; Southern, J.; Laponogov, I.; Higgins, K.; Veselkov, K. Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes. Mach. Learn. Knowl. Extr. 2024, 6, 2738-2752.

6. What ChatGPT Has to Say About Its Topological Structure: The Anyon Hypothesis

ChatGPT对其拓扑结构有何见解：任意子假说

http://www.mdpi.com/2504-4990/6/4/137

Planat, M.; Amaral, M. What ChatGPT Has to Say About Its Topological Structure: The Anyon Hypothesis. Mach. Learn. Knowl. Extr. 2024, 6, 2876-2891.

7. Investigating the Performance of Retrieval-Augmented Generation and Domain-Specific Fine-Tuning for the Development of AI-Driven Knowledge-Based Systems

面向AI驱动知识系统的检索增强生成与领域特定微调性能研究

http://www.mdpi.com/2504-4990/7/1/15

Lakatos, R.; Pollner, P.; Hajdu, A.; Joó, T. Investigating the Performance of Retrieval-Augmented Generation and Domain-Specific Fine-Tuning for the Development of AI-Driven Knowledge-Based Systems. Mach. Learn. Knowl. Extr. 2025, 7, 15.

8. Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques

利用大语言模型辅助非安全专家进行威胁狩猎：检测Living off the Land (LotL)技术

http://www.mdpi.com/2504-4990/7/2/31

Konstantinou, A.; Kasimatis, D.; Buchanan, W.J.; Jan, S.U.; Ahmad, J.; Politis, I.; Pitropakis, N. Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques. Mach. Learn. Knowl. Extr. 2025, 7, 31.

9. Knowledge Graphs and Their Reciprocal Relationship with Large Language Models

知识图谱及其与大语言模型的互惠关系

http://www.mdpi.com/2504-4990/7/2/38

Dehal, R.S.; Sharma, M.; Rajabi, E. Knowledge Graphs and Their Reciprocal Relationship with Large Language Models. Mach. Learn. Knowl. Extr. 2025, 7, 38.

10. A Review of Large Language Models for Automated Test Case Generation

大语言模型在自动化测试用例生成中的应用综述

http://www.mdpi.com/2504-4990/7/3/97

Celik, A.; Mahmoud, Q.H. A Review of Large Language Models for Automated Test Case Generation. Mach. Learn. Knowl. Extr. 2025, 7, 97.

11. Leveraging LLMs for Automated Extraction and Structuring of Educational Concepts and Relationships

利用大语言模型自动提取与构建教育概念及其关系

http://www.mdpi.com/2504-4990/7/3/103

Yang, T.; Ren, B.; Gu, C.; He, T.; Ma, B.; Konomi, S. Leveraging LLMs for Automated Extraction and Structuring of Educational Concepts and Relationships. Mach. Learn. Knowl. Extr. 2025, 7, 103.

12. AlzheimerRAG: Multimodal Retrieval-Augmented Generation for Clinical Use Cases

AlzheimerRAG：面向临床用例的多模态检索增强生成

http://www.mdpi.com/2504-4990/7/3/89

Lahiri, A.K.; Hu, Q.V. AlzheimerRAG: Multimodal Retrieval-Augmented Generation for Clinical Use Cases. Mach. Learn. Knowl. Extr. 2025, 7, 89.

13. Large Language Models for Structured Task Decomposition in Reinforcement Learning Problems with Sparse Rewards

大语言模型在稀疏奖励强化学习问题中的结构化任务分解

http://www.mdpi.com/2504-4990/7/4/126

Ruiz-Gonzalez, U.; Andres, A.; Del Ser, J. Large Language Models for Structured Task Decomposition in Reinforcement Learning Problems with Sparse Rewards. Mach. Learn. Knowl. Extr. 2025, 7, 126.

14. An Overview of Large Language Models and a Novel, Large Language Model-Based Cognitive Architecture for Solving Open-Ended Problems

大语言模型综述及一种基于大语言模型的新型认知架构用于解决开放性问题

http://www.mdpi.com/2504-4990/7/4/134

Shaik, H.; Villuri, G.; Doboli, A. An Overview of Large Language Models and a Novel, Large Language Model-Based Cognitive Architecture for Solving Open-Ended Problems. Mach. Learn. Knowl. Extr. 2025, 7, 134.

15. Context-Aware Emotion Gating and Modulation for Fine-Grained Sentiment Classification

上下文感知情感门控与调制用于细粒度情感分类

http://www.mdpi.com/2504-4990/8/1/9

Thennakoon Mudiyanselage, A.U.G.; Zhang, J.; Li, Y. Context-Aware Emotion Gating and Modulation for Fine-Grained Sentiment Classification. Mach. Learn. Knowl. Extr. 2026, 8, 9.

期刊简介

MAKE (ISSN 2504-4990) 是一个国际型开放获取英文学术期刊，聚焦机器学习和知识提取所有领域相关的研究。期刊发表综述、研究论文、通讯、观点，以及特定主题的特刊。主题领域包括但不限于：机器学习；知识提取；人工智能；神经网络；自然语言处理；无监督学习；隐私保护；不确定性；迁移学习；图像分类；信息检索；特征选择；可视化；基于网络和图的机器学习；几何机器学习与拓扑学；熵及其在机器学习中的应用。