Search Results for author: Antonio Laverghetta Jr.

Found 7 papers, 4 papers with code

No Strong Feelings One Way or Another: Re-operationalizing Neutrality in Natural Language Inference

no code implementations16 Jun 2023 Animesh Nighojkar, Antonio Laverghetta Jr., John Licato

Natural Language Inference (NLI) has been a cornerstone task in evaluating language models' inferential reasoning capabilities.

Natural Language Inference

Predicting Human Psychometric Properties Using Computational Language Models

no code implementations12 May 2022 Antonio Laverghetta Jr., Animesh Nighojkar, Jamshidbek Mirzakhalov, John Licato

In other words, can LMs be of use in predicting the psychometric properties of test items, when those items are given to human participants?

Can Transformer Language Models Predict Psychometric Properties?

1 code implementation Joint Conference on Lexical and Computational Semantics 2021 Antonio Laverghetta Jr., Animesh Nighojkar, Jamshidbek Mirzakhalov, John Licato

We then use the responses to calculate standard psychometric properties of the items in the diagnostic test, using the human responses and the LM responses separately.

Towards a Task-Agnostic Model of Difficulty Estimation for Supervised Learning Tasks

1 code implementation Asian Chapter of the Association for Computational Linguistics 2020 Antonio Laverghetta Jr., Jamshidbek Mirzakhalov, John Licato

Curriculum learning, a training strategy where training data are ordered based on their difficulty, has been shown to improve performance and reduce training time on various NLP tasks.

Natural Language Inference

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