In this presentation, we present the result of our research, where we investigate potential bias in fine-tuned transformer models for irony detection. Bias is defined in this research as spurious associations between word n-grams and class labels, that can cause the system to rely too much on superficial cues and miss the essence of the irony. For this purpose, we looked for correlations between class labels and words that are prone to trigger irony, such as positive adjectives, intensifiers and topical nouns. Additionally, we investigate our irony model’s predictions before and after manipulating the data set through irony trigger replacements. We further support these insights with state-of-the-art explainability techniques (Layer Integrated Gradients, Discretized Integrated Gradients and Layer-wise Relevance Propagation). Both approaches confirm the hypothesis that transformer models generally encode correlations between positive sentiments and ironic texts, with even higher correlations between vividly expressed sentiment and irony. Based on these insights, we implemented a number of modification strategies to enhance the robustness of our irony classifier.

A Fine Line Between Irony and Sincerity: Identifying Bias in Transformer Models for Irony Detection

In this paper, we evaluate a fine-tuned BERT model’s performance on a set of auxiliary probe tasks to gauge whether the model can indirectly encode discourse properties. The focus is on structural properties that have proven important predictors in feature-based Event Coreference Resolution (ECR). We demonstrate that fine-tuning a language model for ECR also increases performance for event prominence and sentiment matching tasks. This contradicts earlier work where coreference models seemed unable to encode any sort of significant structural or discourse information.

What Does BERT actually Learn about Event Coreference? Probing Structural Information in a Fine-Tuned Dutch Language Model

As emotion analysis in text has gained a lot of attention in the field of natural language processing, differences in emotion expression across languages could have consequences for how emotion detection models work. We evaluate the language-dependence of an mBERT-based emotion detection model by comparing language identification performance before and after fine-tuning on emotion detection, and performing (adjusted) zero-shot experiments to assess whether emotion detection models rely on language-specific information. When dealing with typologically dissimilar languages, we found evidence for the language-dependence of emotion detection.

How Language-Dependent is Emotion Detection? Evidence from Multilingual BERT

Event and argument role detection are frequently conceived as separate tasks. In this work we conceive both processes as one task
in a hybrid event detection approach. Its main component is based on automatic keyword extraction (AKE) using the self-attention mechanism of a BERT transformer model. 
As a bottleneck for AKE is defining the threshold of the attention values, we propose a novel method for automatic self-attention threshold
selection. It is fueled by core event information, or simply the verb and its arguments as the backbone of an event. These are outputted by a knowledge-based syntactic parser. In a second
step the event core is enriched with other semantically salient words provided by the transformer model. Furthermore, we propose an automatic self-attention layer and head selection
mechanism, by analyzing which self-attention cells in the BERT transformer contribute most to the hybrid event detection and which linguistic tasks they represent. This approach was integrated in a pipeline event extraction approach
and outperforms three state of the art multi-task event extraction methods.

A Hybrid Knowledge and Transformer-Based Model for Event Detection with Automatic Self-Attention Threshold, Layer and Head Selection

The ability to track fine-grained emotions in customer service dialogues has many real-world applications, but has not been studied extensively. This paper measures the potential of prediction models on that task, based on a real-world dataset of Dutch Twitter conversations in the domain of customer service. We find that modeling emotion trajectories has a small, but measurable benefit compared to predictions based on isolated turns. The models used in our study are shown to generalize well to different companies and economic sectors.

An Emotional Journey: Detecting Emotion Trajectories in Dutch Customer Service Dialogues

In this paper we present baseline results for Event Coreference Resolution (ECR) in Dutch using gold-standard (i.e non-predicted) event mentions. A newly developed benchmark dataset allows us to properly investigate the possibility of creating ECR systems for both within and cross-document coreference. We give an overview of the state of the art for ECR in other languages, as well as a detailed overview of existing ECR resources. Afterwards, we provide a comparative report on our own dataset. We apply a significant number of approaches that have been shown to attain good results for English ECR including feature-based models, monolingual transformer language models and multilingual language models. The best results were obtained using the monolingual BERTje model. Finally, results for all models are thoroughly analysed and visualised, as to provide insight into the inner workings of ECR and long-distance semantic NLP tasks in general.

Investigating Cross-Document Event Coreference for Dutch

In online domain-specific customer service applications, many companies struggle to deploy advanced NLP models successfully, due to the limited availability of and noise in their datasets. While prior research demonstrated the potential of migrating large open-domain pretrained models for domain-specific tasks, the appropriate (pre)training strategies have not yet been rigorously evaluated in such social media customer service settings, especially under multilingual conditions. We address this gap by collecting a multilingual social media corpus containing customer service conversations (865k tweets), comparing various pipelines of pretraining and finetuning approaches, applying them on 5 different end tasks. We show that pretraining a generic multilingual transformer model on our in-domain dataset, before finetuning on specific end tasks, consistently boosts performance, especially in non-English settings.

A Million Tweets Are Worth a Few Points: Tuning Transformers for Customer Support Tasks

Based on a recently developed fine-grained event extraction dataset for the economic domain, we present in a pilot study for supervised economic event extraction. We investigate how a state-of-the-art model for event extraction performs on the trigger and argument identification and classification. While F1-scores of above 50% are obtained on the task of trigger identification, we observe a large gap in performance compared to results on the benchmark ACE05 dataset. We show that single-token triggers do not provide sufficient discriminative information for a fine-grained event detection setup in a closed domain such as economics, since many classes have a large degree of lexico-semantic and contextual overlap.

Extracting Fine-Grained Economic Events from Business News

While it has been claimed that anaphora or coreference resolution plays an important role in opinion mining, it is not clear to what extent coreference resolution actually boosts performance, if at all. In this paper, we investigate the potential added value of coreference resolution for the aspect-based sentiment analysis of restaurant reviews in two languages, English and Dutch. We focus on the task of aspect category classification and investigate whether including coreference
information prior to classification to resolve implicit aspect mentions is beneficial. Because coreference resolution is not a solved task in NLP, we rely on both automatically-derived and gold-standard coreference relations, allowing us to investigate the true upper bound. By training a classifier on a combination of lexical and semantic features, we show that resolving the coreferential relations prior to classification is beneficial in a joint optimization setup. However, this is only the case when relying on gold-standard relations and the result is more outspoken for English than for Dutch. When validating the optimal models, however, we found that only
the Dutch pipeline is able to achieve a satisfying performance on a held-out test set and does so regardless of whether coreference information was included.

It's absolutely divine! Can fine-grained sentiment analysis benefit from coreference resolution?

### [Program](https://wassa-workshop.github.io/2023/schedule/)
Subjectivity and Sentiment Analysis has become a highly developed research area, ranging from binary classification of reviews to the detection of complex emotion structures between entities found in text. This field has expanded both on a practical level, finding numerous successful applications in business, as well as on a theoretical level, allowing researchers to explore more complex research questions related to affective computing. Its continuing importance is also shown by the interest it generates in other disciplines such as Economics, Sociology, Psychology, Marketing, Crisis Management & Digital Humanities. For more details visit our workshop website: https://wassa-workshop.github.io/
#### [Visit GatherTown](https://app.gather.town/app/5OscLswEEuYf2Psb/ACL2023)

W16: The 13th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA)

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.

**Organizers:** Shabnam Tafreshi, University of Maryland: ARLIS; Arjun Reddy Akula, Google; João Sedoc, New York University; Anna Rogers, University of Copenhagen; Aleksandr Drozd, RIKEN; Anna Rumshisky, University of Massachusetts Lowell / Amazon Alexa For more details, please visit our [workshop website](https://insights-workshop.github.io/))

Fourth Workshop on Insights from Negative Results in NLP

### Welcome to the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL) 
Continuing its mission of expanding and involving the science community of all European countries, EACL had selected the Ukrainian community for the 16th EACL, which took place online due to the COVID pandemic. Unfortunately, the ongoing war made the organisation in Kyiv impossible. Considering the importance of physical interaction among researchers, especially after the restrictions imposed by the COVID pandemic, in addition to an online mode, the conference will be held in Dubrovnik, Croatia, from 2 to 6 of May, 2023. The original aim of strengthening the connection with the Ukrainian community will not change as our program will feature a dedicated session and a workshop to highlight work on Ukrainian language technologies. As the flagship European conference in the field of computational linguistics, EACL welcomes European and international researchers covering a broad spectrum of research areas that are concerned with computational approaches to natural language.

You need to register for the conference in order to access this site. Please visit https://2023.eacl.org/registration for more information.

EACL 2023

As the flagship European conference in the field of computational linguistics, EACL welcomes European and international researchers covering a broad spectrum of research areas that are concerned with computational approaches to natural language.

**Chair:** Duygu Ataman **Organizers:** Duygu Ataman, Hila Gonen, Sebastian Ruder, Orhan Firat, Kelechi ogueji, Gözde Gül Sahin and Jamshidbek Mirzakhalov Please visit our [**website**](https://sigtyp.github.io/ws2022-mrl.html) for more information and detailed schedule.

**RocketChat link for this workshop:** https://emnlp2022.rocket.chat/channel/workshop-19-mrl

W19 (MRL) The 2nd Workshop on Multi-lingual Representation Learning

## Welcome to EMNLP 2022!
I am delighted to welcome you to EMNLP 2022! I believe this conference has been complicated beyond any precedent. Over the past year, it’s been thrilling to see the organization team approach each new puzzle with creativity and enthusiasm. We hope that those participating in Abu Dhabi as well as those joining remotely will leave the conference feeling newly inspired by the program and newly connected to our ever-growing community. Following EMNLP 2021 and major NLP conferences since, EMNLP 2022 is “hybrid,” serving both virtual and in-person participants.

Our key innovations for EMNLP 2022 include:

* EMNLP 2022 is “hybrid” in a second sense, as well: we allowed both direct and rolling review paper submissions, building on the pilot experiment of EMNLP 2021, which considered a small number of ARR submissions. 
* Familiar from NAACL but new to EMNLP, we’ve added an industry track.
* During the conference, “portals” will link virtual poster sessions to in-person conference participants during poster sessions each day.
* The first ACL-family conference in the United Arab Emirates.

 *Message from Noah A. Smith, University of Washington and Allen Institute for AI, Seattle, Washington, USA* 
***EMNLP 2022 General Chair***
 
[![](https://assets.underline.io/uploads/markdown_image/1/image/9eec7d4a287ee18c278b08229290aa83.png)](https://drive.google.com/file/d/1OlPv6QBeo62VVTughj2jkiLeyHd1WnUt/view)
 
[![](https://assets.underline.io/uploads/markdown_image/1/image/a3db7a768409f05192210d98601edb25.png)](https://emnlp2022.rocket.chat/)

To access this site you need to register. Please register [here](https://2022.emnlp.org/registration/).

Register here

EMNLP 2022

Welcome!
EMNLP 2022 will take place in Abu Dhabi from December 7th to December 11th, 2022. And it will be held in hybrid mode, both online and offline.

**Chair:** Ali Hürriyetoğlu **Organizers:** Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella, Tadashi Nomoto, Benjamin Radford, Milena Slavcheva, and Erdem Yörük 
**Invited speakers**: [J. Craig Jenkins](https://underline.io/speakers/212902-j.-craig-jenkins), [Scott Althaus](https://underline.io/speakers/212905-scott-althaus) and [Thien Huu Nguyen](https://underline.io/speakers/40729-thien-nguyen)
 Please visit our [**website**](https://emw.ku.edu.tr/case-2022/) for more information and detailed schedule. 
**Rocket channel for this workshop:** https://emnlp2022.rocket.chat/channel/workshop-1-case

 [**Live Session Recording - Day 1**](https://us06web.zoom.us/rec/play/7lXvGAHeFunqc7drItCsNDX8r5dOT-k28zCHHEELV9EytnckOe0wj0GBGitxhcuV4aKlkyTn7UxnsRq4.WDecGUCgdz2bEdW-?autoplay=true&startTime=1670386043000)
 
[**Live Session Recording - Day 2**](https://us06web.zoom.us/rec/play/DuXvqjg035NP1dnOgcQRop3wvW3c4bn_xrxLPineJpgI2Ra_3AKPM7GT1jI-hQlKTvKx4VJAwKjwxrYz.UJa5WCrjg5M2GMLX?autoplay=true&startTime=1670471578000)

W1 (CASE) The 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text 

Click on the Live Session Recording to view the session

**Workshop overview:** The workshop will be co-located with COLING 2022, October 12-17, Gyeongju, Republic of Korea. We will run our event on October 16, in the virtual form, to suit the remote participants, a sizable majority. There will be people on site to help those who attend in person. [**Read more.**](http://noisy-text.github.io/2022/)

W3 8th Workshop on Noisy User-generated Text (W-NUT 2022)

[![](https://assets.underline.io/uploads/markdown_image/1/image/81a3c0317d24f663b49b996875024d45.png)](https://aclanthology.org/volumes/2022.coling-1/)



### THE CONFERENCE WE KNOW AND WE WANT.
**COLING**, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes but also in industrial research departments including tech-startups. COLING provides opportunities for all these communities to showcase their exciting discovery.

In fall of 2022, COLING will be held in Gyeongju in a hybrid format. All participants can either present at the venue site or join virtually. As more people get vaccinated, we are happy to provide safer environments for our colleagues. We believe that COLING 2022 will be one of the conferences, free from the pandemic. The hybrid format gives presenters and sponsors a valuable opportunity to promote their companies in both an online and in-person venue. For the first time in a long time, customers can interact with their sponsor's products first-hand. The online venue, too, gives sponsors the chance to network with those unable to attend the in-person session.

The hybrid format ultimately lends itself to greater exposure for our sponsors: COLING2022 will let you reach more potential partners and customers than ever before!

To gain access to this event page you are required to register. Find more information and pay the registration fee on event the organizer’s website **[https://coling2022.org/reg](https://coling2022.org/reg)**

COLING 2022

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

[Day 1](https://us06web.zoom.us/rec/share/Mn-tEYoJypHCHMPcakmwZZOB_xFuXzO5Ggqheax_P312pFwXLseXPNKCFs8_DpQL.G_4VLfJ11ENXuAG-)
[Day 2](https://us06web.zoom.us/rec/share/Mn-tEYoJypHCHMPcakmwZZOB_xFuXzO5Ggqheax_P312pFwXLseXPNKCFs8_DpQL.G_4VLfJ11ENXuAG-)

**Workshop overview:** After the success of the first shared task on Anaphora Resolution in Dialogues [12], we decided to repeat the shared task on Anaphora Resolution in Dialogues for another time. This shared task provides will have the same tracks as the first one and will have new test data annotated as well as introduce new gold anaphora phrases for the bridging and discourse deixis. More precisely the new shared task provides: 
1. Three Tracks 

* Resolution of anaphoric identity

* Resolution of bridging references

* Resolution of discourse deixis/abstract anaphora

2. Emphasis on less-studied forms of anaphora: Abstract and Bridging

3. Genre: Conversation

4. Computational techniques: transfer of learned representations across genres

5. Opportunities for interaction between communities: Discourse and Dialogue

6. New data set

7. New stages for bridging and discourse deixis with gold anaphors be provided. 
This shared task is jointly run through CRAC 2022 and CODI 2022 at COLING 2022. [**Read more.**](https://codalab.lisn.upsaclay.fr/competitions/614)

W6 Fifth Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC 2022)

**Session Chair: ** Yuval Pinter

1D-Oral: NLP Applications

technical paper

2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics.

**Whova App** 
Stay in touch with your fellow conference attendees via the [Whova App](https://whova.com/portal/webapp/nacon_202106/)

**Conference Structure**
https://2021.naacl.org/blog/conference-structure/

**Walkthrough video of how to NAACL 2021** 

Please take a moment to view this video explaining how to navigate the platform, attend sessions network with other attendees. 


<figure class="video_container">
 <iframe src="https://screencast-o-matic.com/watch/crhwbGVh3vx?v=6&ff=1&title=0&controls=1" width=640 height=350 frameborder="0" allowfullscreen="true"> </iframe>
</figure>

NAACL 2021

The 1st Joint Workshop on Financial Narrative Processing and Multiling Financial Narrative Summarisation (FNP-FNS)

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes, but also in industrial research departments and in technological startups. COLING conferences provide opportunities for all these communities to showcase their exciting developments.

COLING 2020

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

Veronique Hoste

9

8

SHORT BIO

Presentations

A Fine Line Between Irony and Sincerity: Identifying Bias in Transformer Models for Irony Detection

What Does BERT actually Learn about Event Coreference? Probing Structural Information in a Fine-Tuned Dutch Language Model

How Language-Dependent is Emotion Detection? Evidence from Multilingual BERT

A Hybrid Knowledge and Transformer-Based Model for Event Detection with Automatic Self-Attention Threshold, Layer and Head Selection

An Emotional Journey: Detecting Emotion Trajectories in Dutch Customer Service Dialogues

Investigating Cross-Document Event Coreference for Dutch

A Million Tweets Are Worth a Few Points: Tuning Transformers for Customer Support Tasks

Extracting Fine-Grained Economic Events from Business News

It's absolutely divine! Can fine-grained sentiment analysis benefit from coreference resolution?

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