In this paper, we highlight our approach for the "Arabic AI Tasks Evaluation ArAiEval)
Shared Task 2023". We present our approaches for task 1-A and task 2-A of the shared task which focus on persuasion technique detection and disinformation detection respectively. Detection of persuasion techniques and disinformation has become imperative to avoid distortion of authentic information. The tasks use multigenre snippets of tweets and news articles for the given binary classification problem. We experiment with several transformer-based models that were pre-trained on the Arabic language. We fine-tune these state-of-the-art models on the provided dataset. Ensembling is employed to enhance the performance of the systems. We achieved a micro F1-score of 0.742 on task 1-A (8th rank on the leaderboard) and 0.901 on task 2-A (7th rank on the leaderboard) respectively.

Mavericks at ArAIEval Shared Task: Towards a Safer Digital Space - Transformer Ensemble Models Tackling Deception and Persuasion

In this paper, we present our approach for the "Nuanced Arabic Dialect Identification (NADI) Shared Task 2023". We highlight our methodology for subtask 1 which deals with country level dialect identification. Recognizing dialects plays an instrumental role in enhancing the performance of various downstream NLP tasks such as speech recognition and translation. The task uses the Twitter dataset (TWT-2023) that encompasses 18 dialects for the multi-class classification problem. Numerous transformer based models, pre-trained on Arabic language,
are employed for identifying country-level dialects. We fine-tune these state-of-the art models on the provided dataset. The ensembling method is leveraged to yield improved performance of the system. We achieved an F1-score of 76.65 (11th rank on the leaderboard) on the test dataset

Mavericks at NADI 2023 Shared Task: Unravelling Regional Nuances through Dialect Identification using Transformer-based Approach | VIDEO

Mavericks at BLP-2023 Task 1: Ensemble-based Approach Using Language Models for Violence Inciting Text Detection

**[Workshop Organizers:](https://arabicnlp2023.sigarab.org/organizers)**
 *Coffee Break 10:30 am* 
*Lunch Break 12:30 pm* 
*Coffee Break 3:30 pm* [**Workshop Website**](https://arabicnlp2023.sigarab.org/) The First Arabic Natural Language Processing Conference (ArabicNLP 2023) is organized by the Special Interest Group on Arabic NLP (SIGARAB). ArabicNLP 2023 builds on the seven previous workshop editions, which have been extremely successful drawing in a large active participation in various capacities. This conference is timely given the continued rise in research projects focusing on Arabic NLP. [**Schedule**](https://arabicnlp2023.sigarab.org/program)
 [**Go to Gather**](https://app.gather.town/app/ROH1myZvp9ba7a3C/EMNLP2023?spawnToken=Bd1cMzLKR-W1LhrjFP55)

W17: The First Arabic Natural Language Processing Conference (ArabicNLP 2023)

workshop paper

**Welcome to EMNLP 2023!**

On behalf of the EMNLP 2023 Organizing Committee, I extend a warm and heartfelt welcome to all of you to the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP). It is with immense pleasure and excitement that we gather here in Singapore, a vibrant hub of innovation and technological advancement.

The conference program is packed with insightful presentations, thought-provoking workshops, and engaging networking opportunities. In addition to the technical sessions, we have also planned several social events that will provide you with the opportunity to connect with your colleagues.

The conference is held in person at the Resorts World Convention Centre in Singapore, and available on-line with the help of Underline.

For those in Singapore, I hope that you will find time to explore the exciting Sentosa Island, Gardens by the Bay, Singapore Botanic Gardens and the many other attractions unique to Singapore.

Of course, we are grateful to our sponsors and partners for their generous support of EMNLP 2023, whose contributions make it possible for us to host this world-class event.

Yuji Matsumoto (RIKEN AIP) 
EMNLP 2023 General Chair

To access the **EMNLP 2023** event page on Underline, you need to register for the Conference. 
Please follow **[this link](https://2023.emnlp.org/registration/)** for more details.

EMNLP 2023

EMNLP 2023 took place in Singapore from Dec 6th to Dec 10th, 2023.

**Workshop Organizers:** Firoj Alam, Sudipta Kar, Shammur Absar Chowdhury, Farig Sadeque and Mohammad Ruhul Amin
 *Coffee Break 10:30 am* 
*Lunch Break 12:30 pm* 
*Coffee Break 3:30 pm* [**Workshop Website**](https://blp-workshop.github.io/) This workshop aims to provide a forum for researchers to share and discuss their ongoing work with the international community. Following the success of prior local editions of the conferences in 2018 and 2019, in this first edition of the workshop, we will focus on Bangla, which is a low-resource language, and assess its current state-of-the-art and discuss strategies to make further progress in both NLP, Speech and multimodal research. Through this workshop, we plan to bring researchers together to come up with frameworks and strategies that can later support to other low-resource languages. This workshop is timely given the continued rise in research projects focusing on low-resource and multilingual studies. We particularly encourage researchers to submit their papers focusing on novel methodologies and resources that help towards the progress of Bangla and other low-resource languages. Novel methodologies include, but are not limited to, zero-shot learning, unsupervised learning, and simple yet effective methods applicable to low-computation scenarios.
 [**Go to Gather**](https://app.gather.town/app/ROH1myZvp9ba7a3C/EMNLP2023?spawnToken=e0sL3UWeS3q-7dyC3sct)

Sudeep Mangalvedhekar

3

SHORT BIO

Presentations

Mavericks at ArAIEval Shared Task: Towards a Safer Digital Space - Transformer Ensemble Models Tackling Deception and Persuasion

Mavericks at NADI 2023 Shared Task: Unravelling Regional Nuances through Dialect Identification using Transformer-based Approach | VIDEO

Mavericks at BLP-2023 Task 1: Ensemble-based Approach Using Language Models for Violence Inciting Text Detection

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