Papers by Animesh Nighojkar

2 papers
Improving Paraphrase Detection with the Adversarial Paraphrasing Task (2021.acl-long)

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Challenge: a new adversarial method of paraphrase identification is being used to identify paraphrases based on word overlap and syntax . authors propose a dataset that generates semantically equivalent but lexically and syntactically disparate paraphrase pairs .
Approach: They propose an adversarial method for paraphrase identification that uses word overlap and syntax to identify paraphrases.
Outcome: The proposed method improves paraphrase detection accuracy and speed of generation of datasets.
Can Transformer Language Models Predict Psychometric Properties? (2021.starsem-1)

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Challenge: Transformer-based language models (LMs) are gaining popularity on many NLP benchmark tasks.
Approach: They use human responses to calculate psychometric properties of test items . they find transformer-based LMs predict psychometric property consistently well .
Outcome: The transformer-based language models are able to predict psychometric properties of test items . the models can predict psychometries well in certain categories but poorly in others .

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