Topic: To be announced

Speaker: Dr. Ivana Kruijff-Korbayová (F) graduated at the Czech Technical University (1992) and obtained her PhD at the Charles University, Prague (1998). 1999-2000 she held visiting fellowships from the British Academy and Royal Society / NATO at the University of Edinburgh. 2001-2010 she was as a senior researcher at the Department of Computational Linguistics, Saarland University, Saarbrücken. 2012-2023 she coordinated the Erasmus Mundus European Masters Program in Language and Communication Technologies at the Saarland University. 2010-2022 she was a senior researcher in the Multilinguality and Language Technology Lab at the German Research Center for Artificial Intelligence (DFKI) in Saarbrücken, focussing on natural language processing for dialogue systems and human-robot interaction. She lead the Talking Robots Group from 2014 and in 2016 founded the DFKI competence center for Emergency Response and Recovery. She was a coordinator and/or leader in several large projects on robot-assisted disaster response and on 1.9.2016 lead the deployment of a human-robot team in the earthquake-struck Amatrice in Italy. She is a member of the Advisory Board of the International Association of Fire and Rescue Services (CTIF). From January 2023 she is head of research, development and transfer at the German Rescue Robotics Center (DRZ). She has over 70 peer-reviewed publications and h-score 27.

Topic: To be announced

Speaker: Prof. Dr. Hinrich Schuetze is Chair of Computational Linguistics and co-director of the Center for Language and Information Processing at LMU Munich.  Ever since starting his PhD in the early 1990s, Hinrich's research interests have been at the interface of linguistics, cognitive science, neural networks and computer science.  Recent examples include learning with natural language instructions, multilingual representation learning for low-resource languages, computational morphology and neurosymbolic approaches. Hinrich is coauthor of two widely used textbooks (Foundations of Statistical Natural Language Processing and Introduction to Information Retrieval) and a fellow of HessianAI, ELLIS (the European Laboratory for Learning and Intelligent Systems) and ACL (Association for Computational Linguistics).

Topic: To be announced

Speaker: Dr. Marc Schulder is a computational linguist working to further the open and ethical creation and use of language data, especially data for signed languages. After completing his PhD at Saarland University on the automatic creation of lexical resources for negation-causing content words in English and German, he joined the DGS-Korpus project, creators of the largest available discourse corpus of German Sign Language (DGS), in early 2019. As part of the project he investigates machine-assisted methods to support corpus linguistic research, possible implementations of open science principles and data standardisation for signed language data, and the creation of cross-lingual sign language resources. Since 2021 he has also been involved in the EU project EASIER on machine translation between the spoken and signed languages of Europe. Marc is also co-creator of the Sign Language Dataset Compendium, a website collecting information on corpora and lexical resources for sign languages from around the globe, and of the workshop series archive sign-lang@LREC Anthology.

The fast-paced nature of progress in NLP poses unique challenges to educators engaging in curriculum design for NLP courses and NLP-related degree programs. Its rapid growth has led to the creation and revision of thousands of courses and degree programs at universities and online, as well as new educational materials focused on emerging subareas of NLP (e.g., prompting, ethics in NLP systems). For the Workshop on Teaching NLP we propose to bring the NLP community together to discuss crucial topics related to education in NLP.

• Submission deadline: June 9, 2023
• Author notification: July 5, 2023
• Camera ready deadline: July 15, 2023
• Workshop date: September 18, 12pm - 6pm + Workshop Dinner
• Contact: konvens-teach4nlp@googlegroups.com

For more information, visit the official Teaching for NLP Workshop page by the GSCL.

The goal of this shared task is the identification of speakers in political debates and in newswire, and the attribution of speech events, including thought and writing, to their respective speakers.

Being able to identify this information automatically, i.e., identifying who says what to whom, will enable a deep semantic analysis of unstructured text. Specifically, it will help to provide information necessary for identifying speakers and their messages in textual data, a crucial prerequisite for structured text analysis.

• Training and development data release: April 1, 2023
• Test data release (blind): June 15, 2023
• Submissions open: July 1, 2023
• Submissions close: July 31, 2023
• System descriptions due: August 14, 2023
• Camera-ready system paper deadline: September 7, 2023
• Workshop date: September 18, 2023

For more information, visit the official Speaker Attribution 2023 Competition website by Université Paris-Saclay.

The progress of natural language processing (NLP) is primarily driven by machine learning that optimizes a system on a large-scale set of task-specific labeled examples. This learning paradigm limits the ability of machines to have the same capabilities as humans in handling new tasks since humans can often solve unseen tasks with a couple of examples accom-panied by task instruction. In addition, we may not have a chance to prepare task-specific examples of large-volume for new tasks because we cannot foresee what task needs to be ad-dressed next and how complex to annotate for it. Therefore, task instructions act as a noveland promising resource for supervision.

This tutorial targets researchers and practitioners who are interested in AI and ML technologies for NLP generalization in a low-shot scenario. In particular, we will present a diverse thread of instruction-driven NLP studies thattry to answer the following questions: (i) Whatis task instruction? (ii) How to construct task instructions? (iii) How to encode task instruction? (iv) How generalizable are the systems trained on task instructions? (v) How robust is learning from task instructions? We will discuss several lines of frontier research that tackle those challenges and will conclude the tutorialby outlining directions for further investigation.

PDF: Tutorial Description - Learning from Task Instructions

• Tutorial date: September 21, 2023

This workshop focuses on linguistic multimodal phenomena, domain- and task-specific analyses of multimodality and, generally, contributions of computational linguistics to multimodal learning and vice versa. With this, we aim to bring together researchers who work on various linguistic aspects of multimodal language processing to discuss and share the recent advances in this interdisciplinary field.

• Submission deadline : July 07, 2023
• Author notification: August 21, 2023
• Camera ready deadline: September 04, 2023
• Workshop date: September 22, 2023

For more information, visit the official Linguistic Insights from and for Multimodal Language Processing workshop page.

This is the 3rd edition of the workshop on Computational Linguistics for the Political and Social Sciences (CPSS). Our main goal is to bring together researchers and ideas from computational linguistics/NLP and the text-as-data community from political and social science, to foster collaboration and catalyze further interdisciplinary research efforts between these communities.

• Submission deadline: June 14, 2023
• Notification of acceptance: July 10, 2023
• Camera ready deadline: July 20, 2023
• Workshop date: September 22, 2023

For more information, visit the official CPSS workshop page.