3 papers
cs.CL2022
Predicting Human Psychometric Properties Using Computational Language Models
Antonio Laverghetta, Animesh Nighojkar, Jamshidbek Mirzakhalov +1
Transformer-based language models (LMs) continue to achieve state-of-the-art performance on natural language processing (NLP) benchmarks, including tasks designed to mimic human-in…
cs.CL2022
Developmental Negation Processing in Transformer Language Models
Antonio Laverghetta, John Licato
Reasoning using negation is known to be difficult for transformer-based language models. While previous studies have used the tools of psycholinguistics to probe a transformer's ab…
cs.CL2021
Can Transformer Language Models Predict Psychometric Properties?
Antonio Laverghetta, Animesh Nighojkar, Jamshidbek Mirzakhalov +1
Transformer-based language models (LMs) continue to advance state-of-the-art performance on NLP benchmark tasks, including tasks designed to mimic human-inspired "commonsense" comp…