Natural language processing (NLP) has made incredible strides in recent years, particularly through the use of large language models (LLMs). However, one of the primary issues with these LLMs is that they have largely focused on data-rich languages such as English, leaving behind many underrepresented languages and dialects. Moroccan Arabic, also known as Darija, is… →

The routing mechanism of MoE models evokes a great privacy challenge. Optimize LLM large language model performance by selectively activating only a fraction of its total parameters while making it highly susceptible to adversarial data extraction through routing-dependent interactions. This risk, most obviously present with the ECR mechanism, would let an attacker siphon out user… →

Collaborative Filtering (CF) is widely used in recommender systems to match user preferences with items but often struggles with complex relationships and adapting to evolving user interactions. Recently, researchers have explored using LLMs to enhance recommendations by leveraging their reasoning abilities. LLMs have been integrated into various stages, from knowledge generation to candidate ranking. While… →

In today’s world, building robotic policies is difficult. It often requires collecting specific data for each robot, task, and environment, and the learned policies do not generalize beyond these specific settings. Recent progress in open-source, large-scale data collection has made pre-training on large-scale, high-quality, and diverse data possible. However, in robotics, heterogeneity poses a challenge… →

High-performance computing has become crucial for various businesses, including scientific research and Artificial Intelligence (AI), in today’s data-driven society. By providing strong, scalable, and reasonably priced cloud computing resources, GPU hosting companies are essential in enabling these taxing workloads. Selecting the best GPU hosting company is essential for guaranteeing performance, dependability, and cost-effectiveness in light… →

Artificial intelligence has transformed code generation, with large language models (LLMs) for code now integral to software engineering. These models support code synthesis, debugging, and optimization tasks by analyzing vast codebases. However, the development of these code-focused LLMs faces significant challenges. Training requires high-quality instruction-following data, typically gathered through labor-intensive human annotation or leveraging knowledge… →