CONCLUSION: The results of this study support the beneficial effects of an exercise re-education programme, carried out by an interdisciplinary team in improving the autonomy of oncology patients with dyspnoea. →
BACKGROUND: Although natural rubber latex remains dominant as the primary manufacturing material for male condoms synthetic materials first introduced in the early 1990s address many of the limitations of latex including the risk of allergies. Polyurethane elastomers allow condoms to be made significantly thinner to provide greater sensitivity and encourage greater use of condoms for… →
Mixture-of-experts (MoE) architectures are becoming significant in the rapidly developing field of Artificial Intelligence (AI), allowing for the creation of systems that are more effective, scalable, and adaptable. MoE optimizes computing power and resource utilization by employing a system of specialized sub-models, or experts, that are selectively activated based on the input data. Because of… →
Large language models (LLMs) have become fundamental tools for tasks such as question-answering (QA) and text summarization. These models excel at processing long and complex texts, with capacities reaching over 100,000 tokens. As LLMs are popular for handling large-context tasks, ensuring their reliability and accuracy becomes more pressing. Users rely on LLMs to sift through… →
Graph Neural Networks (GNNs) have emerged as the leading approach for graph learning tasks across various domains, including recommender systems, social networks, and bioinformatics. However, GNNs have shown vulnerability to adversarial attacks, particularly structural attacks that modify graph edges. These attacks pose significant challenges in scenarios where attackers have limited access to entity relationships. Despite… →
The paper “MemLong: Memory-Augmented Retrieval for Long Text Modeling” addresses a critical limitation regarding the ability to process long contexts in the field of Large Language Models (LLMs). While LLMs have shown remarkable success in various applications, they struggle with long-sequence tasks due to traditional attention mechanisms’ quadratic time and space complexity. The increasing memory… →
The dynamics governing multi-agent systems (MAS) are complicated and frequently unknown, making the identification of their underlying graph structures a considerable difficulty. Numerous real-world applications, from robotic swarms to distributed sensor networks, use multi-agent systems, which are made up of autonomous agents interacting in a network. Comprehending the network architecture of these systems is essential… →
The primary challenge in scaling large-scale AI systems is achieving efficient decision-making while maintaining performance. Distributed AI, particularly multi-agent reinforcement learning (MARL), offers potential by decomposing complex tasks and distributing them across collaborative nodes. However, real-world applications face limitations due to high communication and data requirements. Traditional methods, like model predictive control (MPC), require precise… →
Hallucination is a phenomenon where large language models (LLMs) produce responses that are not grounded in reality or do not align with the provided context, generating incorrect, misleading, or nonsensical information. These errors can have serious consequences, particularly in applications that require high precision, like medical diagnosis, legal advice, or other high-stakes scenarios. As the… →
DeepSeek-AI has released DeepSeek-V2.5, a powerful Mixture of Experts (MOE) model with 238 billion parameters, featuring 160 experts and 16 billion active parameters for optimized performance. The model excels in chat and coding tasks, with cutting-edge capabilities such as function calls, JSON output generation, and Fill-in-the-Middle (FIM) completion. With an impressive 128k context length, DeepSeek-V2.5… →