For many languages and applications, even though enough data is available for training Named Entity Disambiguation (NED) systems, few off-the-shelf models are available for use in practice. This is due to both the large size of state-of-the-art models, and to the computational requirements for recreating them from scratch. However, we observe that in practice, acceptable models can be trained and run with far fewer resources. In this work, we intro- duce MiniNED, a framework for creating small NED models from medium-sized datasets. The resulting models can be tuned for application- specific objectives and trade-offs, depending on practitioners’ requirements concerning model size, frequency bias, and out-of-domain gener- alization. We evaluate the framework in nine languages, and achieve reasonable performance using models that are a fraction of the size of recent work.

Minimalist Entity Disambiguation for Mid-Resource Languages
Benno Kruit (b.b.kruit@vu.nl)
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.

Benno Kruit

1

SHORT BIO

Presentations

Minimalist Entity Disambiguation for Mid-Resource Languages Benno Kruit (b.b.kruit@vu.nl) Status: Accept

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES