15 citations · 33 across the 6 of their papers we have counts for
5 papers · 1 filter
Fully Automated Identification of Lexical Alignment and Preference-Stage Shifts in Large Language Models
Thomas Stephan Juzek, Xiaoyang Ming, Jose A. Hernandez
The language used by digital chat assistants such as ChatGPT can diverge from human expectations (misalignment). Research, mostly on Scientific English, has described both what div…
Isolating LLM Lexical Bias: A Curation-Free Triangulated Metric for Preference-Stage Learning
Xiaoyang Ming, Jose Hernandez, Thomas Stephan Juzek
Various language domains have undergone remarkable changes in recent years; these shifts are largely attributed to the advent of Large Language Models and their misalignment with n…
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…
Establishing Vocabulary Tests as a Benchmark for Evaluating Large Language Models
Gonzalo Martínez, Javier Conde, Elena Merino-Gómez +4
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…
How many words does ChatGPT know? The answer is ChatWords
Gonzalo Martínez, Javier Conde, Pedro Reviriego +3
The introduction of ChatGPT has put Artificial Intelligence (AI) Natural Language Processing (NLP) in the spotlight. ChatGPT adoption has been exponential with millions of users ex…