Evaluating the performance of Massively Multilingual Language Models (MMLMs) is difficult due to the shortage of evaluation datasets in low-resource languages. Due to computational limitations evaluating MMLMs trained on all possible pivot configurations is not feasible. This paper describes our contribution to the SumEval 2022 shared task, which handles the crucial task of Performance prediction of MMLMs. We build upon Microsoft Research's Project LITMUS and devise a method to further improve predictions. We develop various machine-learning approaches which outperform the baseline score provided by LITMUS. Our system ranked first with an RMSE score of 0.017 for the non-surprise and 0.109 for the surprise dataset.

To Train or Not to Train: Predicting the Performance of Massively Multilingual Models

Detecting emotions in languages is important to accomplish a complete interaction between humans and machines. This paper describes our contribution to the WASSA 2022 shared task which handles this crucial task of emotion detection. We have to identify the following emotions: sadness, surprise, neutral, anger, fear, disgust, joy based on a given essay text. We are using an ensemble of ELECTRA and
BERT models to tackle this problem achieving an F1 score of 62.76%.

Transformer based ensemble for emotion detection

This paper aims to perform an emotion analysis of social media comments in Tamil. Emotion analysis is the process of identifying the emotional context of the text. In this paper, we present the findings obtained by Team Optimize_Prime in the ACL 2022 shared task "Emotion Analysis in Tamil." The task aimed to classify social media comments into categories of emotion like Joy, Anger, Trust, Disgust, etc. The task was further divided into two subtasks, one with 11 broad categories of emotions and the other with 31 specific categories of emotion. We implemented three different approaches to tackle this problem: transformer-based models, Recurrent Neural Networks (RNNs), and Ensemble models. XLM-RoBERTa performed the best on the first task with a macro-averaged f1 score of 0.27, while MuRIL provided the best results on the second task with a macro-averaged f1 score of 0.13.

Emotion Analysis in Tamil

This paper tries to address the problem of abusive comment detection in low-resource indic languages. Abusive comments are statements that are offensive to a person or a group of people. These comments are targeted toward individuals belonging to specific ethnicities, genders, caste, race, sexuality, etc. Abusive Comment Detection is a significant problem, especially with the recent rise in social media users. This paper presents the approach used by our team - Optimize_Prime, in the ACL 2022 shared task "Abusive Comment Detection in Tamil." This task detects and classifies YouTube comments in Tamil and Tamil- English Codemixed format into multiple categories. We have used three methods to optimize our results: Ensemble models, Recurrent Neural Networks, and Transformers. In the Tamil data, MuRIL and XLM-RoBERTA were our best performing models with a macro-averaged f1 score of 0.43. Furthermore, for the Code-mixed data, MuRIL and M-BERT provided sub-lime results, with a macro-averaged f1 score of 0.45.

Abusive Comment Detection in Tamil

[![](https://assets.underline.io/uploads/markdown_image/1/image/d3ad15ab8ad93db2e42d31f48e79049f.png)](https://us06web.zoom.us/rec/play/QR1bjSINsXtoCwhY664nr5uaTfXm14Onn-Sga7UXDiB7Xfk_nIRJxAg2rtpbocm42p7a1evwF-L7lZ_I.LMv_oBcNWWJGQ2Ob?autoplay=true&startTime=1668939300000) 
[![](https://assets.underline.io/uploads/markdown_image/1/image/4fb65ba99e2b22744cbf88050198d474.png)](https://us06web.zoom.us/rec/play/H5ktPEVrL38GW8kc0uTOAcAA1NsSzLYfOiUleYV2t2PAfooBgSf_PJWFmeZo4eocHAWFOifUjAdmCoqM.Lf8MG-Crb7SVndZ_?autoplay=true&startTime=1668966531000)
 
 **Workshop Organizers:**
 Daniel Deutsch, Can Udomcharoenchaikit, Alex Gaskell, Marina Fomicheva, Steffen Eger, and Yang Gao

Third Workshop on Evaluation and Comparison of NLP Systems

workshop paper

The AACL, Asia-Pacific Chapter of the Association for Computational Linguistics, and the AFNLP, Asian Federation of Natural Language Processing, invite you to participate in the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL) and the 10th International Joint Conference on Natural Language Processing (IJCNLP).

A registration is required to access this event. Access to the event site will be granted to all registered attendees on **November 16th**. If you have not already done so, please register using the link below:
 
 https://conference.iis.sinica.edu.tw/servlet/Register?ConferenceID=411

Registration Is Required

IJCNLP-AACL 2022

The AACL, Asia-Pacific Chapter of the Association for Computational Linguistics, and the AFNLP, Asian Federation of Natural Language Processing, invite you to participate in the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL) and the 10th International Joint Conference on Natural Language Processing (IJCNLP). 

**Organizers:** Jeremy Barnes, Orphée De Clercq, Valentin Barriere, Shabnam Tafreshi, Sawsan Alqahtani,
João Sedoc, Roman Klinger, Alexandra Balahur
 **Description:** Starting with reviews on products on e-commerce sites and ending with the emotional effect presentin or intended by
media coverage, research in automatic Subjectivity and Sentiment Analysis as wellas explicit and implicit Emotion Detection and Classification has flourished in the past years. Theimportance of the field has been proven by the high number
of approaches proposed in research in thepast decade, as well as by the interest it generated in other disciplines, such as
Economics, Sociology,Psychology, Marketing, Crisis Management Digital Humanities. Building on previous editions,
the aim of WASSA 2022 is to bring together researchers workingon Subjectivity, Sentiment Analysis, Emotion Detection and Classification and their applications toother NLP or real-world tasks (e.g. public health messaging, fake news,
media impact analysis, socialmedia mining, computational literary studies) and researchers working on interdisciplinary
aspectsof affect computation from text.
 
**Please visit our [website](https://wassa-workshop.github.io/)**

(WASSA) The 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis

# Welcome everyone to ACL 2022!

The 60th Annual Meeting of the Association for Computational Linguistics is taking place May 22-27, 2022 as a hybrid event, in Dublin and online. We are happy to welcome all of you to this anniversary edition with an almost 50-50 in-person and virtual participation. 
The main conference program features oral presentations, in-person and virtual posters and demo sessions, a plenary session for our best paper presentations and awards, three amazing keynote events and two new initiatives of invited talks: Spotlight Talks for Young Rising Stars (STIRS) and The Next Big Idea Talks. Posters (including Findings of ACL 2022) and demos are grouped by areas for both the in-person and the virtual sessions. For the virtual component, the talks will be on Zoom and the posters and the demos will be in GatherTown. The Student Research Workshop will have an oral session and a poster session as part of Poster Session 1. The program also features eight Tutorials and 28 Workshops. 

 
We wish you a wonderful conference! 
[**The ACL 2022 Organizing Committee**](https://www.2022.aclweb.org/organisers)
 
[**Conference Handbook**](https://drive.google.com/file/d/1_BUCMfhMVrjG9E2e71aHdHeE28KSje0l/view?usp=sharing) 
[**Mini Handbook**](https://drive.google.com/file/d/1qlBKl0wzmlVF1oCeMQl3BahLd9nLP5Ce/view?usp=sharing) 
[**Posters and Demo guides**](https://drive.google.com/file/d/1UucMAoCNncIOaH1rMMDa0owuG9qgvJTG/view?usp=sharing)

ACL 2022

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 (NLP). 

**Organizers:** Bharathi Raja Chakravarthi, Ruba Priyadharshini, Anand Kumar M, Parameswari
Krishnamurthy, Elizabeth Sherly, Sinnathamby Mahesan
 **Description:** The development of technology increases our internet use, and most of the global languages have adapted themselves
to the digital era. However, there are many regional, under-resourced languages that face challenges as they still lack
developments in language technology [1]. One such language family is the Dravidian family of languages. Dravidian
languages are primarily spoken in south India and Sri Lanka. Pockets of speakers are found in Nepal, Pakistan, Malaysia,
other parts of India and elsewhere in the world. The Dravidian languages, which are 4,500 years old [2] and spoken by
millions of speakers, are under-resourced in speech and natural language processing [1]. The Dravidian languages are
divided into four groups: South, South-Central, Central, and North groups. Dravidian morphology is agglutinating and
exclusively suffixal. Syntactically, Dravidian languages are head-final and left-branching. They are free-constituent order
languages. To improve access to and production of information for monolingual speakers of Dravidian languages, it is
necessary to have speech and languages technologies. The aim of these workshops is to save the Dravidian languages
from extinction in technology. This is the first workshop on speech and language technologies for Dravidian languages.
 
**Please visit our [website](https://dravidianlangtech.github.io/2022/)**

Shantanu Patankar

4

4

SHORT BIO

Presentations

To Train or Not to Train: Predicting the Performance of Massively Multilingual Models

Transformer based ensemble for emotion detection

Emotion Analysis in Tamil

Abusive Comment Detection in Tamil

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES