most citedUnderstanding the Impact of Artificial Intelligence in Academic Writing: Metadata to the Rescue

14 citations · 32 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL202512 cited

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…

cs.AI202514 cited

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…

cs.CL20256 cited

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…

cs.MM2024

Analyzing Recursiveness in Multimodal Generative Artificial Intelligence: Stability or Divergence?

Javier Conde, Tobias Cheung, Gonzalo Martínez +2

One of the latest trends in generative Artificial Intelligence is tools that generate and analyze content in different modalities, such as text and images, and convert information…

cs.CL2024

Evaluating Large Language Models with Tests of Spanish as a Foreign Language: Pass or Fail?

Marina Mayor-Rocher, Nina Melero, Elena Merino-Gómez +3

Large Language Models (LLMs) have been profusely evaluated on their ability to answer questions on many topics and their performance on different natural language understanding tas…