14 citations · 58 across the 11 of their papers we have counts for
5 papers · 1 filter
Stochastic Streets: A Walk Through Random LLM Address Generation in four European Cities
Tairan Fu, David Campo-Nazareno, Javier Coronado-Blázquez +3
Large Language Models (LLMs) are capable of solving complex math problems or answer difficult questions on almost any topic, but can they generate random street addresses for Europ…
Energy-Efficient Stochastic Computing (SC) Neural Networks for Internet of Things Devices With Layer-Wise Adjustable Sequence Length (ASL)
Ziheng Wang, Pedro Reviriego, Farzad Niknia +4
Stochastic computing (SC) has emerged as an efficient low-power alternative for deploying neural networks (NNs) in resource-limited scenarios, such as the Internet of Things (IoT).…
Speed and Conversational Large Language Models: Not All Is About Tokens per Second
Javier Conde, Miguel González, Pedro Reviriego +3
The speed of open-weights large language models (LLMs) and its dependency on the task at hand, when run on GPUs, is studied to present a comparative analysis of the speed of the mo…
Understanding the Impact of Artificial Intelligence in Academic Writing: Metadata to the Rescue
Javier Conde, Pedro Reviriego, Joaquín Salvachúa +3
This column advocates for including artificial intelligence (AI)-specific metadata on those academic papers that are written with the help of AI in an attempt to analyze the use of…
Can ChatGPT Learn to Count Letters?
Javier Conde, Gonzalo Martínez, Pedro Reviriego +3
Large language models (LLMs) struggle on simple tasks such as counting the number of occurrences of a letter in a word. In this paper, we investigate if ChatGPT can learn to count…