Existing discourse corpora are annotated based on different frameworks, which show significant dissimilarities in definitions of arguments and relations and structural constraints. Despite differences at surface level, these discourse models share some assumptions, such as the role of discourse relations. Studies that explore
correlations between discourse relation inventories are hindered by different segmentation criteria, and expert knowledge and manual examination are typically needed. In this paper, we introduce a fully automatic approach to address the challenges. Specifically, we extend the label-anchored contrastive learning method proposed by Zhang et al. (2022) to learn label embeddings during a classification task. These embeddings are then utilized to map discourse relations from different frameworks.

Learning Label Embeddings for Mapping Discourse Relations of Different Annotation Frameworks (Extended Abstract)

Discourse information is difficult to represent and annotate. Among the major frameworks for annotating discourse information, RST, PDTB and SDRT are widely discussed and used, each having its own theoretical foundation and focus. The motivation of unifying the frameworks, challenges of the task and my research questions will be discussed in the presentation.

 Towards Unification of Discourse Annotation Frameworks

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The last ten years have seen a dramatic improvement in the ability of NLP systems to understand and produce words and sentences. This development has created a renewed interest in discourse phenomena as researchers move towards the processing of long-form text and conversations. There is a surge of activity in discourse parsing, coherence models, text summarization, corpora for discourse level reading comprehension, and discourse related/aided representation learning, to name a few, but the problems in computational approaches to discourse are still substantial. At this juncture, we have organized four Workshops on Computational Approaches to Discourse (CODI) at EMNLP 2020, EMNLP 2021, COLING 2022 and ACL 2023 to bring together discourse experts and upcoming researchers. These workshops have catalyzed work to improve the speed and knowledge needed to solve such problems and have served as a forum for the discussion of suitable datasets and reliable evaluation methods. [**Read more**](https://sites.google.com/view/codi2024/). [**Invited Speakers**](https://sites.google.com/view/codi2024/invited-speakers) **Program Overview** 
09:15 - 09:30 Opening Remarks 
09:30 - 10:30 Invited Talk - Hannah Rohde: Inferences of additional coherence-driven meaning within and across clauses 
10:30 - 11:00 Coffee Break 
11:00 - 12:00 Poster Session 1 
12:00 - 13:30 Lunch 
13:30 - 14:30 Invited Talk - Manfred Stede: Connectives and Arguments 
14:30 - 15:30 Poster Session 2 
15:30 - 16:00 Coffee Break 
16:00 - 17:30 Session - Oral presentations 
17:30 - 17:45 Closing Remarks [**Detailed Program**](https://sites.google.com/view/codi2024/schedule)

W1: 5th Workshop on Computational Approaches to Discourse (CODI)

workshop paper

Welcome to the 18th 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 has selected the Malta community for the 18th EACL. Considering the importance of physical interaction among researchers, the conference will be held at the Hotel Radisson Blu, St. Julians, in Malta, from 17 to 22 of March, 2024. The conference will also feature the possibility to participate virtually. 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. 
#### [Conference Handbook](https://drive.google.com/file/d/13Wn38q0yev6U3RTgnf4Tn5T9GuAuZ-xW/view?usp=sharing) *downloadable*

To access the EACL 2024 event page you need to register [**here**](https://acl.swoogo.com/EACL2024). 

Please register!

EACL 2024

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.

Posters: Student Research Workshop

poster

# 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). 

Yingxue Fu

2

Presentations

Learning Label Embeddings for Mapping Discourse Relations of Different Annotation Frameworks (Extended Abstract)

Towards Unification of Discourse Annotation Frameworks

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