Language Models for Hierarchical Classification of Radiology Reports with Attention Mechanisms, BERT and GPT-4
Radiology reports are a valuable source of textual information used to improve clinical care
and support research. In recent years, deep learning techniques have been shown to be …
and support research. In recent years, deep learning techniques have been shown to be …
UniGen: A Unified Framework for Textual Dataset Generation Using Large Language Models
Large Language Models (LLMs) such as GPT-4 and Llama3 have significantly impacted
various fields by enabling high-quality synthetic data generation and reducing dependence …
various fields by enabling high-quality synthetic data generation and reducing dependence …
A Strategy Labelled Dataset of Counterspeech
A Poudhar, I Konstas… - Proceedings of the 8th …, 2024 - aclanthology.org
Increasing hateful conduct online demands effective counterspeech strategies to mitigate its
impact. We introduce a novel dataset annotated with such strategies, aimed at facilitating the …
impact. We introduce a novel dataset annotated with such strategies, aimed at facilitating the …
Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions
X Yang, G Li, J Li - arXiv preprint arXiv:2406.10573, 2024 - arxiv.org
Graph Neural Networks (GNNs) have significantly advanced various downstream graph-
relevant tasks, encompassing recommender systems, molecular structure prediction, social …
relevant tasks, encompassing recommender systems, molecular structure prediction, social …
Smart Expert System: Large Language Models as Text Classifiers
Text classification is a fundamental task in Natural Language Processing (NLP), and the
advent of Large Language Models (LLMs) has revolutionized the field. This paper …
advent of Large Language Models (LLMs) has revolutionized the field. This paper …
PGA-SciRE: Harnessing LLM on Data Augmentation for Enhancing Scientific Relation Extraction
Y Zhou, S Shan, H Wei, Z Zhao, W Feng - arXiv preprint arXiv:2405.20787, 2024 - arxiv.org
Relation Extraction (RE) aims at recognizing the relation between pairs of entities mentioned
in a text. Advances in LLMs have had a tremendous impact on NLP. In this work, we propose …
in a text. Advances in LLMs have had a tremendous impact on NLP. In this work, we propose …
Artificial Data, Real Insights: Evaluating Opportunities and Risks of Expanding the Data Ecosystem with Synthetic Data
R Timpone, Y Yang - arXiv preprint arXiv:2408.15260, 2024 - arxiv.org
Synthetic Data is not new, but recent advances in Generative AI have raised interest in
expanding the research toolbox, creating new opportunities and risks. This article provides a …
expanding the research toolbox, creating new opportunities and risks. This article provides a …
Prompt Refinement or Fine-tuning? Best Practices for using LLMs in Computational Social Science Tasks
Large Language Models are expressive tools that enable complex tasks of text
understanding within Computational Social Science. Their versatility, while beneficial, poses …
understanding within Computational Social Science. Their versatility, while beneficial, poses …
Event Extraction Based on Self-Data Augmentation with Large Language Models
L Yang, X Fan, X Wang, X Wang, Q Chen - 2024 - researchsquare.com
Event extraction plays a crucial role in natural language processing (NLP), facilitating the
transformation of unstructured text into structured representations. This conversion …
transformation of unstructured text into structured representations. This conversion …
Integrated Predictive Modeling and Analytics for Crisis Management
AA Alhamadani - 2024 - vtechworks.lib.vt.edu
The surge in the application of big data and predictive analytics in fields of crisis
management, such as pandemics and epidemics, highlights the vital need for advanced …
management, such as pandemics and epidemics, highlights the vital need for advanced …