3 papers
cs.CL2026
How does fine-tuning improve sensorimotor representations in large language models?
Minghua Wu, Javier Conde, Pedro Reviriego +1
Large Language Models (LLMs) exhibit a significant "embodiment gap", where their text-based representations fail to align with human sensorimotor experiences. This study systematic…
cs.CL2025
Adding LLMs to the psycholinguistic norming toolbox: A practical guide to getting the most out of human ratings
Javier Conde, MarÃa Grandury, Tairan Fu +7
Word-level psycholinguistic norms lend empirical support to theories of language processing. However, obtaining such human-based measures is not always feasible or straightforward.…
cs.CL2025
Psycholinguistic Word Features: a New Approach for the Evaluation of LLMs Alignment with Humans
Javier Conde, Miguel González, MarÃa Grandury +3
The evaluation of LLMs has so far focused primarily on how well they can perform different tasks such as reasoning, question-answering, paraphrasing, or translating. For most of th…