Assessing Open-Source Large Language Models on Argumentation Mining Subtasks

no code implementations • 8 Nov 2024 • Mohammad Yeghaneh Abkenar, Weixing Wang, Hendrik Graupner, Manfred Stede

We explore the capability of four open-sourcelarge language models (LLMs) in argumentation mining (AM).

ARC Relation Classification

SeCoKD: Aligning Large Language Models for In-Context Learning with Fewer Shots

no code implementations • 20 Jun 2024 • Weixing Wang, Haojin Yang, Christoph Meinel

Previous studies have shown that demonstrations can significantly help Large Language Models (LLMs ) perform better on the given tasks.

In-Context Learning Self-Knowledge Distillation

Feature Distribution Shift Mitigation with Contrastive Pretraining for Intrusion Detection

no code implementations • 23 Apr 2024 • Weixing Wang, Haojin Yang, Christoph Meinel, Hasan Yagiz Özkan, Cristian Bermudez Serna, Carmen Mas-Machuca

In recent years, there has been a growing interest in using Machine Learning (ML), especially Deep Learning (DL) to solve Network Intrusion Detection (NID) problems.

Network Intrusion Detection