Search Results for author: Orion Weller

Found 10 papers, 6 papers with code

When to Use Multi-Task Learning vs Intermediate Fine-Tuning for Pre-Trained Encoder Transfer Learning

1 code implementation ACL 2022 Orion Weller, Kevin Seppi, Matt Gardner

We find that there is a simple heuristic for when to use one of these techniques over the other: pairwise MTL is better than STILTs when the target task has fewer instances than the supporting task and vice versa.

Multi-Task Learning

Exploring the Relationship Between Algorithm Performance, Vocabulary, and Run-Time in Text Classification

1 code implementation NAACL 2021 Wilson Fearn, Orion Weller, Kevin Seppi

Text classification is a significant branch of natural language processing, and has many applications including document classification and sentiment analysis.

Classification Document Classification +3

Streaming Models for Joint Speech Recognition and Translation

no code implementations EACL 2021 Orion Weller, Matthias Sperber, Christian Gollan, Joris Kluivers

However, all previous work has only looked at this problem from the consecutive perspective, leaving uncertainty on whether these approaches are effective in the more challenging streaming setting.

Automatic Speech Recognition speech-recognition +1

You Don't Have Time to Read This: An Exploration of Document Reading Time Prediction

no code implementations ACL 2020 Orion Weller, Hildebr, Jordan t, Ilya Reznik, Christopher Challis, E. Shannon Tass, Quinn Snell, Kevin Seppi

Predicting reading time has been a subject of much previous work, focusing on how different words affect human processing, measured by reading time.

The rJokes Dataset: a Large Scale Humor Collection

no code implementations LREC 2020 Orion Weller, Kevin Seppi

We also introduce this dataset as a task for future work, where models learn to predict the level of humor in a joke.

Humor Detection: A Transformer Gets the Last Laugh

2 code implementations IJCNLP 2019 Orion Weller, Kevin Seppi

These experiments show that this method outperforms all previous work done on these tasks, with an F-measure of 93. 1% for the Puns dataset and 98. 6% on the Short Jokes dataset.

Humor Detection

Cannot find the paper you are looking for? You can Submit a new open access paper.