Deductive software architecture recovery via chain-of-thought prompting

SA Rukmono, L Ochoa, M Chaudron - … of the 2024 ACM/IEEE 44th …, 2024 - dl.acm.org
As software evolves, software architecture recovery techniques can help for effective
maintenance. We envision a deductive software architecture recovery approach supported …

Exploiting LLM Embeddings for Content-Based IoT Anomaly Detection

T Wang, Z Zhao, K Wu - 2024 IEEE Pacific Rim Conference on …, 2024 - ieeexplore.ieee.org
The Internet of Things (IoT) consists of enormous special-purpose devices whose security is
hard to guarantee due to their simple design. Compared to data content on the Internet, the …

Explaining learning to rank methods to improve them

A Veneri - Proceedings of the 32nd ACM International …, 2023 - dl.acm.org
State-of-the-art methods for Learning to Rank (LtR), either designed for tabular or textual
data, are incredibly complex. Increasing the complexity of the models has many drawbacks …

Exploring the Intersection of Large Language Models (LLMs) and Explainable AI (XAI): A Systematic Literature Review (Research-in-Progress)

BL Sebin, NA Taskin, N Mehdiyev - 2024 - aisel.aisnet.org
In the evolving domain of natural language processing (NLP), the emergence of Large
Language Models (LLMs) like Generative Pre-trained Transformer (GPT), Bidirectional …