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.
This article presents two frameworks for combating issues with fine-grained vehicle recognition (FGVR) caused by image noise. The first, a progressive multi-task anti-noise learning (PMAL) framework, improves recognition accuracy by…
Continue readingThis article investigates the experiences of individuals who have used Large Language Model (LLM) chatbots for mental health support. The authors conducted interviews with 21 globally diverse individuals and analyzed…
Continue readingThis article discusses the concept of Autonomous Supply Chains (ASCs), which are being considered as a more resilient alternative to traditional supply chains. The authors present a formal definition of…
Continue readingThe paper presents a novel framework, CAFFEINE, aimed at improving response generation in long-term conversations by refining speaker personas. Traditional methods often yield uninformative persona sentences that limit response quality….
Continue readingThe paper addresses the challenge of extending Large Language Models (LLMs) to non-English languages, especially those using non-Latin scripts. The authors propose using the romanized form of text as an…
Continue readingThe paper introduces TDFNet, a model for audio-visual speech separation. This technology is significant for applications like speech recognition and assistive technologies. While existing methods demand more computational resources and…
Continue readingThis research focuses on utilizing liver CT scans in colorectal carcinoma genomics mutation classification. The liver is the most affected organ by distant metastasis in colon-rectal cancer patients. The study…
Continue readingThe study presents a new framework, ‘CAFFEINE’, to resolve issues in long-term conversation. It focuses on refining contradictory personas into sentences that contain rich speaker information based on their contextual…
Continue readingThe paper presents a study testing the portability of task-specific knowledge encoded in modules trained by parameter-efficient finetuning (PEFT) techniques. Using sentiment analysis as an example, the authors conduct 1,440…
Continue readingThe article discusses AR-GAN, a Generative Adversarial Network-based defense method against adversarial attacks on the Traffic Sign Classification System of Autonomous Vehicles. The AR-GAN classification system includes a generator that…
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