The recently introduced FNet model (Lee-Thorp et al., 2022) computes a two-dimensional discrete Fourier transform (DFT) of a sequence- length-by-hidden-dimension-sized representation of its input. Because it is equally efficient to compute the DFT of any reshaping of this input matrix, we investigate the extent to which increasing the frequency resolution in one dimension (at the expense of the other) affects task performance. We consider the LRA tasks (Tay et al., 2021) considered by Lee-Thorpe et al., as well as the more practical setting of using FNet as the encoder in a machine translation (MT) model. We find that frequency resolution has a marked task-dependent effect on performance, allowing us to largely outperform standard FNet on our tasks, and suggesting that resolution should be carefully tuned before deploying FNet.

Exploring the Effect of Frequency Resolution in FNet
Gregory Szumel, Ghazal Khalighinejad, Rickard Stureborg and Sam Wiseman (gks9@duke.edu)
Status: Accept

The Natural Language Processing (NLP) community has, in recent years, demonstrated a notable focus on improving higher scores on standard benchmarks and taking the lead on community-wide leaderboards (e.g., GLUE, SentEval). While this aspiration has led to improvements in benchmark performance of (predominantly neural) models, it has also came at a cost, i.e., increased model complexity and the ever-growing amount of computational resources required for training and using the current state-of-the-art models. Moreover, the recent research efforts have, for the most part, failed to identify sources of empirical gains in models, often failing to empirically justify the model complexity beyond benchmark performance

Because of these easily observable trends, we have proposed the SustaiNLP workshop with the goal of promoting more sustainable NLP research and practices, with two main objectives: (1) encouraging development of more efficient NLP models; and (2) providing simpler architectures and empirical justification of model complexity. For both aspects, we will encourage submissions from all topical areas of NLP.

 For more details visit our workshop website: https://sites.google.com/view/sustainlp2023
#### [Visit GatherTown](https://app.gather.town/app/5OscLswEEuYf2Psb/ACL2023)

W6: The 4th Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)

workshop paper

### Welcome to ACL 2023, the 61st Annual Meeting of the Association for Computational Linguistics! 
 The conference will be held in Toronto, Canada, July 9-14, 2023. 
Following the succession of the recent conferences in our field, ACL 2023 will adopt a hybrid format.
While the impact of Covid has considerably diminished in terms of traveling, obtaining visas to Canada
entails a very long process. Moreover, the global economic conditions pose challenges for many individuals to travel to conferences. Recognizing these circumstances, we know many participants may not be
able to attend the conference in person. Therefore, we are committed to providing a great virtual platform
so everyone has the opportunity to interact with other participants and enjoy the conference. Based on the
current registered participants, approxiately 30% have chosen to attend the conference virtually. Whether
you join us in person or virtually, we sincerely hope everyone has a remarkable conference experience. 
This General Chair’s message is where I express my gratitude to the many individuals who have made
enormous contributions to the conference over the past year.

Read [**ACL 2023 General Chair's message**](https://docs.google.com/document/d/1WobYM7norbG4dI48s75HfJoD89qgX5a_F-6U8AteLSA/edit?usp=sharing/) in full.

##### **[Conference Handbook](https://2023.aclweb.org/downloads/acl2023-handbook.pdf)**

ACL 2023

The Association for Computational Linguistics (ACL) is the premier international scientific and professional society for people working on computational problems involving human language, a field often referred to as either computational linguistics or natural language processing.

Gregory Szumel

1

SHORT BIO

Presentations

Exploring the Effect of Frequency Resolution in FNet Gregory Szumel, Ghazal Khalighinejad, Rickard Stureborg and Sam Wiseman (gks9@duke.edu) Status: Accept

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES