Search Results for author: Priyanka Sen

Found 7 papers, 3 papers with code

Speech Disfluencies occur at Higher Perplexities

no code implementations COLING (CogALex) 2020 Priyanka Sen

Speech disfluencies have been hypothesized to occur before words that are less predictable and therefore more cognitively demanding.

Language Modelling

Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering

1 code implementation COLING 2022 Priyanka Sen, Alham Fikri Aji, Amir Saffari

We introduce Mintaka, a complex, natural, and multilingual dataset designed for experimenting with end-to-end question-answering models.

Question Answering

Expanding End-to-End Question Answering on Differentiable Knowledge Graphs with Intersection

1 code implementation EMNLP 2021 Priyanka Sen, Amir Saffari, Armin Oliya

End-to-end question answering using a differentiable knowledge graph is a promising technique that requires only weak supervision, produces interpretable results, and is fully differentiable.

Knowledge Graphs Question Answering

End-to-End Entity Resolution and Question Answering Using Differentiable Knowledge Graphs

no code implementations EMNLP 2021 Armin Oliya, Amir Saffari, Priyanka Sen, Tom Ayoola

Our model only needs the question text and the answer entities to train, and delivers a stand-alone QA model that does not require an additional ER component to be supplied during runtime.

Entity Resolution Knowledge Graphs +1

What do Models Learn from Question Answering Datasets?

1 code implementation EMNLP 2020 Priyanka Sen, Amir Saffari

While models have reached superhuman performance on popular question answering (QA) datasets such as SQuAD, they have yet to outperform humans on the task of question answering itself.

Question Answering Reading Comprehension

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