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20202025
most citedProbing the Natural Language Inference Task with Automated Reasoning Tools

2 citations · 5 across the 5 of their papers we have counts for

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cs.CL2023

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

Animesh Nighojkar, Antonio Laverghetta, John Licato

Natural Language Inference (NLI) has been a cornerstone task in evaluating language models' inferential reasoning capabilities. However, the standard three-way classification schem…

cs.CL2022★ 1 cited

Cognitive Modeling of Semantic Fluency Using Transformers

Animesh Nighojkar, Anna Khlyzova, John Licato

Can deep language models be explanatory models of human cognition? If so, what are their limits? In order to explore this question, we propose an approach called hyperparameter hyp…

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.CL2021

Improving Paraphrase Detection with the Adversarial Paraphrasing Task

Animesh Nighojkar, John Licato

If two sentences have the same meaning, it should follow that they are equivalent in their inferential properties, i.e., each sentence should textually entail the other. However, m…

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…