Event-related potential (ERP), a specialized paradigm of electroencephalographic (EEG), reflects neurological responses to external stimuli or events, generally...
Althoughthereislittleempiricalresearchonplatform-specific performance for retail workloads, the digital transformation of the retail industry has accelerated th...
In this article, we explore federated customization of large models and highlight the key challenges it poses within the federated learning framework. We review...
Large Language Model (LLM)-based applications are increasingly deployed across various domains, including customer service, education, and mobility. However, th...
The primary value of AI agents in software development lies in their ability to extend the developer's capacity for reasoning and action, not to supplant human ...
Autonomous coding agents are increasingly deployed as AI teammates in modern software engineering, independently authoring pull requests (PRs) that modify produ...
Model-driven engineering (MDE) provides abstraction and analytical rigour, but industrial adoption in many domains has been limited by the cost of developing an...
Advances in artificial intelligence (AI) and deep learning have raised concerns about its increasing energy consumption, while demand for deploying AI in mobile...
This paper explores the complexities of automatic detection of software similarities, in relation to the unique challenges of digital artifacts, and introduces ...
The quadratic complexity of self-attention mechanism presents a significant impediment to applying Transformer models to long sequences. This work explores comp...
We propose the Consensus-Based Privacy-Preserving Data Distribution (CPPDD) framework, a lightweight and post-setup autonomous protocol for secure multi-client ...
Deploying LLMs efficiently requires testing hundreds of serving configurations, but evaluating each one on a GPU cluster takes hours and costs thousands of doll...
