30 citations · 94 across the 30 of their papers we have counts for
9 papers · 1 filter
Why Do Large Language Models (LLMs) Struggle to Count Letters?
Tairan Fu, Raquel Ferrando, Javier Conde +2
Large Language Models (LLMs) have achieved unprecedented performance on many complex tasks, being able, for example, to answer questions on almost any topic. However, they struggle…
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…
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…
Using large language models to estimate features of multi-word expressions: Concreteness, valence, arousal
Gonzalo Martínez, Juan Diego Molero, Sandra González +3
This study investigates the potential of large language models (LLMs) to provide accurate estimates of concreteness, valence and arousal for multi-word expressions. Unlike previous…
Recursive InPainting (RIP): how much information is lost under recursive inferences?
Javier Conde, Miguel González, Gonzalo Martínez +3
The rapid adoption of generative artificial intelligence (AI) is accelerating content creation and modification. For example, variations of a given content, be it text or images, c…
Spanish and LLM Benchmarks: is MMLU Lost in Translation?
Irene Plaza, Nina Melero, Cristina del Pozo +4
The evaluation of Large Language Models (LLMs) is a key element in their continuous improvement process and many benchmarks have been developed to assess the performance of LLMs in…
Concurrent Linguistic Error Detection (CLED): a New Methodology for Error Detection in Large Language Models
Jinhua Zhu, Javier Conde, Zhen Gao +3
The wide adoption of Large language models (LLMs) makes their dependability a pressing concern. Detection of errors is the first step to mitigating their impact on a system and thu…
Open Conversational LLMs do not know most Spanish words
Javier Conde, Miguel González, Nina Melero +5
The growing interest in Large Language Models (LLMs) and in particular in conversational models with which users can interact has led to the development of a large number of open-s…
Beware of Words: Evaluating the Lexical Diversity of Conversational LLMs using ChatGPT as Case Study
Gonzalo Martínez, José Alberto Hernández, Javier Conde +2
The performance of conversational Large Language Models (LLMs) in general, and of ChatGPT in particular, is currently being evaluated on many different tasks, from logical reasonin…