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Found 19 papers, 2 papers with code
Real-time Spatial Retrieval Augmented Generation for Urban Environments
The use case serves to validate the correct integration of Foundation Models through the proposed RAG architecture.
Speed and Conversational Large Language Models: Not All Is About Tokens per Second
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 most popular open LLMs.
Can ChatGPT Learn to Count Letters?
Large language models (LLMs) struggle on simple tasks such as counting the number of occurrences of a letter in a word.
Understanding the Impact of Artificial Intelligence in Academic Writing: Metadata to the Rescue
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 such tools for disseminating research.
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
In this paper, we study how the LLM confidence in its answer depends on whether the model has been asked to answer directly or to provide the reasoning before answering.
Enhanced FIWARE-Based Architecture for Cyberphysical Systems With Tiny Machine Learning and Machine Learning Operations: A Case Study on Urban Mobility Systems
This article extends a previous architecture based on FIWARE software components to implement the machine learning operations flow, enabling the management of the entire tinyML lifecycle in cyberphysical systems.
Evaluation of real-time transcriptions using end-to-end ASR models
For this reason, it is necessary to design and test different splitting algorithms to optimize the quality and delay of the resulting transcription.
Evaluating Large Language Models with Tests of Spanish as a Foreign Language: Pass or Fail?
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 tasks.
Adaptive Resolution Inference (ARI): Energy-Efficient Machine Learning for Internet of Things
This enables most inferences to run with the reduced precision model and only a small fraction requires the full model, so significantly reducing computation and energy while not affecting model performance.
Applying digital twins for the management of information in turnaround event operations in commercial airports
The aerospace sector is one of the many sectors in which large amounts of data are generated.
Using large language models to estimate features of multi-word expressions: Concreteness, valence, arousal
In Study 1, ChatGPT-4o showed strong correlations with human concreteness ratings (r = . 8) for multi-word expressions.
How Stable is Stable Diffusion under Recursive InPainting (RIP)?
This process of recursively applying inpainting can lead to an image that is similar or completely different from the original one, depending on the fragments that are removed and the ability of the model to reconstruct them.
Spanish and LLM Benchmarks: is MMLU Lost in Translation?
Selected categories of the benchmark are translated into Spanish using Azure Translator and ChatGPT4 and run on ChatGPT4.
Concurrent Linguistic Error Detection (CLED) for Large Language Models
Since the proposed error detection mechanism only relies on the outputs of the model, then it can be used on LLMs in which there is no access to the internal nodes.
Open Conversational LLMs do not know most Spanish words
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-source chat LLMs.
Beware of Words: Evaluating the Lexical Diversity of Conversational LLMs using ChatGPT as Case Study
In this paper, we consider the evaluation of the lexical richness of the text generated by LLMs and how it depends on the model parameters.
Establishing Vocabulary Tests as a Benchmark for Evaluating Large Language Models
Vocabulary tests, once a cornerstone of language modeling evaluation, have been largely overlooked in the current landscape of Large Language Models (LLMs) like Llama, Mistral, and GPT.
How many words does ChatGPT know? The answer is ChatWords
The benefits of ChatWords are illustrated with two case studies: evaluating the knowledge that ChatGPT has of the Spanish lexicon (taken from the official dictionary of the "Real Academia Espa\~nola") and of the words that appear in the Quixote, the well-known novel written by Miguel de Cervantes.
Playing with Words: Comparing the Vocabulary and Lexical Richness of ChatGPT and Humans
Therefore, further research is needed to understand how the use of ChatGPT and more broadly generative AI tools will affect the vocabulary and lexical richness in different types of text and languages.
