Search Results for author: Andrew Mattarella-Micke

Found 2 papers, 1 papers with code

Do Long-Range Language Models Actually Use Long-Range Context?

no code implementations • EMNLP 2021 • Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke, Mohit Iyyer

Language models are generally trained on short, truncated input sequences, which limits their ability to use discourse-level information present in long-range context to improve their predictions.

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Exploring and Predicting Transferability across NLP Tasks

1 code implementation • EMNLP 2020 • Tu Vu, Tong Wang, Tsendsuren Munkhdalai, Alessandro Sordoni, Adam Trischler, Andrew Mattarella-Micke, Subhransu Maji, Mohit Iyyer

We also develop task embeddings that can be used to predict the most transferable source tasks for a given target task, and we validate their effectiveness in experiments controlled for source and target data size.

Language Modelling Part-Of-Speech Tagging +4

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