It is the subfield of computer science that focuses on creating systems capable of intelligent behavior, including problem solving, learning, adaptation, perception, and language understanding.
The paper presents ‘Ta keed’, an Arabic automatic fact-checking system that not only classifies information as true or false but also provides explanations for its classifications. The system utilises two…
Continue readingThe article presents CompactifAI, a novel compression method for Large Language Models (LLMs) like ChatGPT and LlaMA. LLMs are advancing rapidly in AI, but their large size leads to significant…
Continue readingThe article presents a novel fine-tuning paradigm called BayesPrompt. It is designed to improve pre-trained language models’ (PLMs) performance on downstream tasks. The existing problem is that prompt-tuning methods fail…
Continue readingThe paper introduces a novel framework, CAFFEINE, for managing and refining personas in long-term conversations. It addresses the issue of uninformative persona sentences in human-authored datasets by leveraging commonsense-based persona…
Continue readingThis study explores the extension of Large Language Models (LLMs) to non-English languages, specifically those using non-Latin scripts. The proposed approach uses the romanized form of text as an interface…
Continue readingThis paper proposes a system that utilizes Vehicle-to-Everything (V2X) technology for autonomous vehicles to exchange data and make real-time decisions. The system also operates a federated learning scheme to create…
Continue readingThe study focuses on the development of an attack-resilient Generative Adversarial Network (AR-GAN) for traffic sign classification in autonomous vehicles (AVs). AVs rely on Deep Neural Network (DNN)-based systems to…
Continue readingThe study introduces CAFFEINE, a context-aware refinement framework for contradictory personas in long-term conversations. This framework aims to improve dialogue systems by refining and expanding personas based on their contextual…
Continue readingAVs utilize deep neural network (DNN)-based classification systems to identify traffic signs. However, these models are susceptible to adversarial attacks that can cause misclassification by introducing slight perturbations to an…
Continue readingThe study addresses the challenge of extending Large Language Models (LLMs) to non-English languages, specifically those using non-Latin scripts. An innovative approach that utilizes the romanized form of text as…
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