Provisional Programme

Monday 23 June - Workshops and Tutorials
09:00 - 12:30
3rd International Workshop on Gender-Inclusive Translation Technologies (GITT 2025)
Programme
1st Workshop on Artificial Intelligence and Easy and Plain Language in Institutional Contexts
Programme
Tutorial: Understanding Large Language Model-Generated Translations
More info
12:30 - 13:30 Lunch Break
13:30 - 17:30
(continued) 3rd International Workshop on Gender-Inclusive Translation Technologies (GITT 2025)
(continued) 1st Workshop on Artificial Intelligence and Easy and Plain Language in Institutional Contexts
Tutorial: Leveraging Examples in Machine Translation
More info
Tuesday 24 June - Workshops and Tutorials
09:00 - 12:30
2nd Workshop on Creative-text Translation and Technology (CTT 2025)
Programme
3rd International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)
Programme
11th Workshop on Patent and Scientific Literature Translation (PSLT 2025)
Programme
12:30 - 13:30 Lunch Break
13:30 - 17:30
(continued) 2nd Workshop on Creative-text Translation and Technology (CTT 2025)
(continued) 3rd International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)
Tutorial: Best practices for data quality in human annotation of translation datasets
More info
18:30 - Welcome Reception
Wednesday 25 June - Main Conference
09:00 - 09:30 Opening Ceremony
09:30 - 10:30

Keynote Speech: Sarah Ebling, University of Zurich (UZH)

In this talk, I will highlight the challenges of automatic translation between spoken languages and sign languages, touching on the topics of representation, data, and ethics. Additionally, I will introduce preprocessing tasks and discuss their state of the art. I will present research conducted in our group in the different areas.

10:30 - 11:00 Coffee Break
11:00 - 12:30

Parallel sessions:

Session chair: [to be defined]

  • Name Consistency in LLM-based Machine Translation of Historical Texts
    Dominic P. Fischer and Martin Volk
  • Do not change me: On transferring entities without modification in neural machine translation - a multilingual perspective
    Dawid Wiśniewski, Mikołaj Pokrywka and Zofia Rostek
  • Metaphors in Literary Machine Translation: Close but no cigar?
    Alina Karakanta, Mayra Nas and Aletta G. Dorst

Session chair: [to be defined]

  • Optimising ChatGPT for creativity in literary translation: A case study from English into Dutch, Chinese, Catalan and Spanish
    Shuxiang Du, Ana Guerberof Arenas, Antonio Toral, Kyo Gerrits and Josep Marco Borillo
  • To MT or not to MT: An eye-tracking study on the reception by Dutch readers of different translation and creativity levels
    Kyo Gerrits and Ana Guerberof-Arenas
  • Extending CREAMT: Leveraging Large Language Models for Literary Translation Post-Editing
    Antonio Castaldo, Sheila Castilho, Joss Moorkens and Johanna Monti
12:30 - 13:30 Lunch Break
13:30 - 15:00

Parallel sessions:

Session chair: [to be defined]

  • Investigating Length Issues in Document-level Machine Translation
    Ziqian Peng, Rachel Bawden and François Yvon
  • Context-Aware or Context-Insensitive? Assessing LLMs’ Performance in Document-Level Translation
    Wafaa Mohammed and Vlad Niculae
  • Context-Aware Monolingual Evaluation of Machine Translation
    Silvio Picinini and Sheila Castilho

Session chair: [to be defined]

  • Improving MT-enabled Triage Performance with Multiple MT Outputs
    Marianna J. Martindale and Marine Carpuat
  • ITALERT: Assessing the Quality of LLMs and NMT in Translating Italian Emergency Response Text
    Maria Carmen Staiano, Lifeng Han, Johanna Monti and Francesca Chiusaroli
  • Translation Analytics for Freelancers: I. Introduction, Data Preparation, Baseline Evaluations
    Yuri Balashov, Alex Balashov and Shiho Fukuda Koski
15:00 - 15:30

Sponsored Talk: STAR Group

STAR Group
Diana Ballard and Julian Hamm
15:30 - 16:00 Coffee Break
16:00 - 17:30

Parallel sessions:

Session chair: [to be defined]

  • Decoding Machine Translationese in English-Chinese News: LLMs vs. NMTs
    Delu Kong and Lieve Macken
  • Instruction-tuned Large Language Models for Machine Translation in the Medical Domain
    Miguel Angel Rios Gaona
  • Improving Japanese-English Patent Claim Translation with Clause Segmentation Models based on Word Alignment
    Masato Nishimura, Kosei Buma, Takehito Utsuro and Masaaki Nagata

Session chair: [to be defined]

  • Using AI Tools in Multimedia Localization Workflows: a Productivity Evaluation
    Ashley Mondello, Romina Cini, Sahil Rasane, Alina Karakanta and Laura Casanellas
  • Speech-to-Speech Translation Pipelines for Conversations in Low-Resource Languages
    Andrei Popescu-Belis, Alexis Allemann, Teo Ferrari and Gopal Krishnamani
  • A comparison of translation performance between DeepL and Supertext
    Alex Flückiger, Chantal Amrhein, Tim Graf, Frédéric Odermatt, Martin Pömsl, Philippe Schläpfer, Florian Schottmann and Samuel Läubli
18:00 - Conference Tour
Thursday 26 June - Main Conference
09:00 - 10:00

Parallel sessions:

Session chair: [to be defined]

  • Languages Transferred Within the Encoder: On Representation Transfer in Zero-Shot Multilingual Translation
    Zhi Qu, Chenchen Ding and Taro Watanabe
  • Progressive Perturbation with KTO for Enhanced Machine Translation of Indian Languages
    Yash Bhaskar, Ketaki Shetye, Vandan Mujadia, Dipti Misra Sharma and Parameswari Krishnamurthy

Session chair: [to be defined]

  • Using Translation Techniques to Characterize MT outputs
    Sergi Alvarez-Vidal, Maria Do Campo, Christian Olalla-Soler and Pilar Sanchez-Gijon
  • The Challenge of Translating Culture-Specific Items: Evaluating MT and LLMs Against Human Translators
    Bojana Budimir
10:00 - 10:30 Sponsored Talk: World Intellectual Property Organization (WIPO)
10:30 - 11:00 Coffee Break
11:00 - 11:30 Best Thesis Award
11:30 - 12:30 Poster Boaster
12:30 - 13:30 Lunch Break
13:30 - 14:30

Poster session:

  • Investigating the translation capabilities of Large Language Models trained on parallel data only
    Javier García Gilabert, Carlos Escolano, Aleix Sant, Francesca De Luca Fornaciari, Audrey Mash, Xixian Liao and Maite Melero
  • Lingonberry Giraffe: Lexically-Sound Beam Search for Explainable Translation of Compound Words
    Théo Salmenkivi-Friberg and Iikka Hauhio
  • Leveraging Visual Scene Graph to Enhance Translation Quality in Multimodal Machine Translation
    Ali Hatami, Mihael Arcan and Paul Buitelaar
  • Culture-aware machine translation: the case study of low-resource language pair Catalan-Chinese
    Xixian Liao, Carlos Escolano, Audrey Mash, Francesca De Luca Fornaciari, Javier García Gilabert, Miguel Claramunt Argote, Ella Bohman and Maite Melero
  • Non-autoregressive Modeling for Sign-gloss to Texts Translation
    Fan Zhou and Tim Van de Cruys
  • Exploring the Feasibility of Multilingual Grammatical Error Correction with a Single LLM up to 9B parameters: A Comparative Study of 17 Models
    Dawid Wiśniewski, Artur Nowakowski and Antoni Solarski
  • Intrinsic vs. Extrinsic Evaluation of Sentence Embeddings: Semantic Relevance Doesn't Help with MT Evaluation
    Petra Barančíková and Ondřej Bojar

  • Can postgraduate translation students identify machine-generated text?
    Michael Farrell
  • MT or not MT? Do translation specialists know a machine-translated text when they see one?
    Rudy Loock, Nathalie Moulard and Quentin Pacinella
  • Human- or machine-translated subtitles: Who can tell them apart?
    Ekaterina Lapshinova-Koltunski, Sylvia Jaki, Merle Sauter and Maren Bolz

  • SpeechT: Findings of the First Mentorship in Speech Translation
    Yasmin Moslem, Juan Julián Cea Morán, Mariano Gonzalez-Gomez, Muhammad Hazim Al Farouq, Farah Abdou and Satarupa Deb
  • Replacing the Irreplaceable: A Case Study of Limitations Shown by AI and MT during the 2023 Israel-Gaza Conflict
    Abeer Alfaify

  • HPLT’s Second Data Release
    Nikolay Arefyev, Mikko Aulamo, Marta Bañón, Laurie Burchell, Pinzhen Chen, Mariia Fedorova, Ona de Gibert, Liane Guillou, Barry Haddow, Jan Hajič, Jindřich Helcl, Erik Henriksson, Andrei Kutuzov, Veronika Laippala, Jelmer Van der Linde, Bhavitvya Malik, Farrokh Mehryary, Vladislav Mikhailov, Amanda Myntti, Dayyán O'Brien, Stephan Oepen, Sampo Pyysalo, Gema Ramírez-Sánchez, David Samuel, Pavel Stepachev, Jörg Tiedemann, Dušan Variš, Tereza Vojtěchová and Jaume Zaragoza-Bernabeu
  • ProMut: The Evolution of NMT Didactic Tools
    Pilar Sánchez-Gijón and Gema Ramírez-Sánchez
  • Reverso Define: An AI-Powered Contextual Dictionary for Professionals
    Quentin Pleplé and Théo Hoffenberg
  • GAMETRAPP project in progress: Designing a virtual escape room to enhance skills in research abstract post-editing
    Cristina Toledo-Báez and Luis Carlos Marín-Navarro
  • UniOr PET: An Online Platform for Translation Post-Editing
    Antonio Castaldo, Sheila Castilho, Joss Moorkens and Johanna Monti
  • Machine translation as support for epistemic capacities: Findings from the DECA project
    Maarit Koponen, Nina Havumetsä, Juha Lång and Mary Nurminen
  • AI4Culture platform: upskilling experts on multilingual / -modal tools
    Tom Vanallemeersch, Sara Szoc, Marthe Lamote, Frederic Everaert and Eirini Kaldeli
  • eSTÓR: Curating Irish Datasets for Machine Translation
    Abigail Walsh, Órla Ní Loinsigh, Jane Adkins, Ornait O'Connell, Mark Andrade, Teresa Clifford, Federico Gaspari, Jane Dunne and Brian Davis
  • OPAL Enable: Revolutionizing Localization Through Advanced AI
    Mara Nunziatini, Konstantinos Karageorgos, Aaron Schliem and Mikaela Grace
  • DeMINT: Automated Language Debriefing for English Learners via AI Chatbot Analysis of Meeting Transcripts
    Miquel Esplà-Gomis, Felipe Sánchez-Martínez, Víctor M. Sánchez-Cartagena and Juan Antonio Pérez-Ortiz
14:30 - 15:30

Keynote Speech: Eva Vanmassenhove, Tilburg University (TiU)

Language is humanity’s primary tool to preserve and transmit knowledge, evolving alongside and with cultural technologies. Today, multilingual large language models (LLMs) represent the latest leap. Emerging evidence, however, suggests that LLMs might subtly (or not so subtly) distort language over time, amplifying frequent patterns while eroding linguistic richness,  a phenomenon linked to model collapse which had already been observed in Neural Machine Translation (NMT) systems even before it was formally named. Unlike the visible artefacts that have already been observed in the AI-generated images created by computer vision models, linguistic shifts, such as the loss of the long tails of language, risk going unnoticed. Yet, they mayhave profound implications for language, translation, diversity, and the integrity of communication across different languages. This keynote will explore these ideas and connect them to specific translation issues, asking: What is (or will be) at stake when our world of words becomes increasingly shaped by multilingual LLMs.

15:30 - 16:00 Coffee Break
16:00 - 17:30 EAMT/ IAMT general assembly
19:30 - Conference Dinner
Friday 27 June - Main Conference
09:00 - 10:30

Parallel sessions:

Session chair: [to be defined]

  • OJ4OCRMT: A Large Multilingual Dataset for OCR-MT Evaluation
    Paul McNamee, Kevin Duh, Cameron Carpenter, Ron Colaianni, Nolan King and Kenton Murray
  • Testing LLMs' Capabilities in Annotating Translations Based on an Error Typology Designed for LSP Translation: First Experiments with ChatGPT
    Joachim Minder, Guillaume Wisniewski and Natalie Kübler
  • Synthetic Fluency: Examining Hallucinations in LLM-Generated Irish Translations
    Sheila Castilho, Zoe Fitzsimmons, Claire Holton and Aoife Mc Donagh

Session chair: [to be defined]

  • Is it AI or PE that worry translation professionals: results from a Human-Centered AI survey
    Miguel A. Jimenez-Crespo and Stephanie Rodriguez
  • Revisiting Post-Editing for English-Chinese Machine Translation
    Hari Venkatesan
  • The GAMETRAPP project: Spanish scholars’ perspectives and attitudes towards neural machine translation and post-editing
    Cristina Toledo-Báez and Luis Carlos Marín-Navarro

Session chair: [to be defined]

  • Cultural Transcreation in Asian Languages with Prompt-Based LLMs
    Helena Wu, Beatriz Silva, Vera Cabarrão and Helena Moniz
  • Arabizi vs LLMs: Can the Genie Understand the Language of Aladdin?
    Perla Al Almaoui, Pierrette Bouillon and Simon Hengchen
  • Leveraging LLMs for Cross-Locale Adaptation: a Workflow Proposal on Spanish Variants
    Vera Senderowicz Guerra
10:30 - 11:00 Coffee Break
11:00 - 12:00

Keynote Speech: Joss Moorkens, Dublin City University (DCU)

This talk reflects on ethical issues with MT using LLMs, looking particularly at a recent evaluation study in the medical domain. This study, and the potential for its findings to be used as a basis for action, bring abstract ethical issues into focus. More broadly, the heightened attention and potential for impact of MT and LLM research brings an added sense of responsibility for researchers, although this might be balanced with opportunities to contribute to the common good.

12:00 - 12:30

Sponsored Talk: BIG Language

BIG Language
Maciej Modrzejewski, Machine Learning Architect at BIG

As localization demands scale across industries, the pressure to deliver high-quality translations faster, without compromising accuracy or compliance, is intensifying. In this talk, we explore how generative AI is not just enhancing but fundamentally redefining localization workflows.
We’ll show how combining Neural Machine Translation (NMT) with Large Language Models (LLMs) and guiding them with smart Quality Estimation and workflow automation creates a more efficient, scalable localization process. From automatic post-editing and source quality improvement to adaptive QA routing and feedback-driven learning loops, this system optimizes quality and efficiency.
You’ll see how strategic interventions like context-aware routing, selective human review, and multi-format content processing enable localization teams to shift from reactive editing to proactive content consulting. We’ll share real-world results, including reduced Edit Distance, faster post-editing times, and measurable quality gains across accounts.
The future of localization is hybrid, intelligent, and strategically human.

12:30 - 13:30 Lunch Break
13:30 - 14:30 Poster Boaster
14:30 - 15:30

Poster Session:

  • Patent Claim Translation via Continual Pre-training of Large Language Models with Parallel Data
    Haruto Azami, Minato Kondo, Takehito Utsuro and Masaaki Nagata
  • The Devil is in the Details: Assessing the Effects of Machine-Translation on LLM Performance in Domain-Specific Texts
    Javier Osorio, Afraa Alshammari, Naif Alatrush, Dagmar Heintze, Amber Converse, Sultan Alsarra, Latifur Khan, Patrick T. Brandt and Vito D'Orazio
  • Improve Fluency Of Neural Machine Translation Using Large Language Models
    Jianfei He, Wenbo Pan, Jijia Yang, Sen Peng and Xiaohua Jia
  • Optimizing the Training Schedule of Multilingual NMT using Reinforcement Learning
    Alexis Allemann, Àlex R. Atrio and Andrei Popescu-Belis
  • bytF: How Good Are Byte Level N-Gram F-Scores for Automatic Machine Translation Evaluation?
    Raj Dabre, Kaing Hour and Haiyue Song
  • Are AI agents the new machine translation frontier? Challenges and opportunities of single- and multi-agent systems for multilingual digital communication
    Vicent Briva-Iglesias
  • Quality Estimation and Post-Editing Using LLMs For Indic Languages: How Good Is It?
    Anushka Singh, Aarya Pakhale, Mitesh M. Khapra and Raj Dabre

  • Introducing Quality Estimation to Machine Translation Post-editing Workflow: An Empirical Study on Its Usefulness
    Siqi Liu, Guangrong Dai and Dechao Li
  • Investigating the Integration of LLMs into Trainee Translators’ Practice and Learning: A Questionnaire-based Study on Translator-AI Interaction
    Xindi Hao and Shuyin Zhang
  • Prompt engineering in translation: How do student translators leverage GenAI tools for translation tasks
    Jia Zhang, Xiaoyu Zhao and Stephen Doherty

  • MTUOC server: integrating several NMT and LLMs \\into professional translation workflows
    Antoni Oliver
  • The BridgeAI Project
    Helena Moniz, Joana Lamego, Nuno André and Antonio Novais
  • Machine Translation to Inform Asylum Seekers: Intermediate Findings from the MaTIAS Project
    Lieve Macken, Ella van Hest, Arda Tezcan, Michaël Lumingu, Katrijn Maryns and July De Wilde
  • FLORES+ Mayas: Generating Textual Resources to Foster the Development of Language Technologies for Mayan Languages
    Andrés Lou, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Miquel Esplà-Gomis and Víctor M. Sánchez-Cartagena
  • ZuBidasoa: Participatory Research for the Development of Linguistic Technologies Adapted to the Needs of Migrants in the Basque Country
    Xabier Soto, Ander Egurtzegi, Maite Oronoz and Urtzi Etxeberria
  • MaTOS: Machine Translation for Open Science
    Rachel Bawden, Maud Bénard, Eric de la Clergerie, José Cornejo Cárcamo, Nicolas Dahan, Manon Delorme, Mathilde Huguin, Natalie Kübler, Paul Lerner, Alexandra Mestivier, Joachim Minder, Jean-François Nominé, Ziqian Peng, Laurent Romary, Panagiotis Tsolakis, Lichao Zhu and François Yvon
  • CAT-GPT: A Skopos-Driven, LLM-Based Computer-Assisted Translation Tool
    Paşa Abdullah Bayramoğlu
  • MTxGames: Machine Translation Post-Editing in Video Game Translation – First Preliminary Results on Productivity and Translator Experience
    Judith Brenner
  • Prompt-based Explainable Quality Estimation for English-Malayalam
    Archchana Sindhujan, Diptesh Kanojia and Constantin Orasan
  • Reverso Documents, The New Generation Document Translation Platform
    Elodie Segrestan and Théo Hoffenberg
15:30 - 16:00 Coffee Break
16:00 - 17:00 Closing ceremony, including IAMT Award of Honour, Best Paper Award. Announcement: EAMT 2026, MT Summit 2027

Keynote speakers


Sarah Ebling

Wednesday, 25 June (9.30 am - 10.30 am) — see in programme

Sarah Ebling is Full Professor of Language, Technology and Accessibility at the University of Zurich. Based in the field of computational linguistics, her research focuses on language-based assistive technologies in the context of persons with disabilities. Specifically, Sarah Ebling's research takes place in the context of deafness and hearing impairment, blindness and visual impairment, cognitive impairment, and language disorders. She is conducting research on sign language technologies, automatic text simplification, technologies for the audio description process, and computer-aided language sample analysis.
Sarah Ebling is involved in international and national projects and is the PI of a large-scale Swiss innovation project entitled "Inclusive Information and Communication Technologies" (2022-2026; https://www.iict.uzh.ch/).


Joss Moorkens

Friday, 27 June (11 am - 12 pm) — see in programme

Joss Moorkens is an Associate Professor at the School of Applied Language and Intercultural Studies in Dublin City University (DCU), Science Lead at the ADAPT Centre, and member of DCU’s Institute of Ethics and Centre for Translation and Textual Studies. He has published over 60 articles and papers on the topics of translation technology interaction and evaluation, translator precarity, and translation ethics. He is General Co-Editor of the journal Translation Spaces with Prof. Dorothy Kenny, co-editor of a number of books and journal special issues, and co-author of the textbooks Translation Tools and Technologies (Routledge 2023) and Automating Translation (Routledge 2024). He sits on the board of the European Masters in Translation Network.


Eva Vanmassenhove

Tilburg University (TiU)

Eva Vanmassenhove

Thursday, 26 June (2.30 pm - 3.30 pm) — see in programme

Eva Vanmassenhove is a researcher specializing in Machine Translation and Language Technology, with a strong focus on tackling gender and algorithmic biases in translation systems. She earned her PhD from Dublin City University and now serves as an assistant professor in the Department of Cognitive Science and Artificial Intelligence at Tilburg University (TiU). At TiU, she contributes to the Computation and Psycholinguistics Research unit and the Inclusive and Sustainable Machine Translation Research Line. Her work aims to enhance machine translation by addressing biases, especially in gender representation, while preserving linguistic richness.


Workshops

The following workshops will take place on 23-24 June.


1st Workshop on Artificial Intelligence and Easy and Plain Language in Institutional Contexts (AI & EL/PL)

Monday, 23 June (9 am - 5 pm)

This full-day workshop will delve into cutting-edge technologies that advance the production of Easy and Plain Language, with a particular emphasis on Automatic Text Simplification (ATS) and the role of Large Language Models (LLMs) in generating, validating, and refining accessible communication across institutional contexts. Participants will gain a comprehensive understanding of how AI is revolutionising accessible communication, particularly through its applications in Easy and Plain Language. The workshop will offer insights into AI's potential to automate and optimise language simplification processes, while also fostering a collaborative environment for professionals to exchange best practices and experiences. By engaging with like-minded peers, attendees will be equipped to develop innovative, collaborative solutions that enhance their future work and drive progress in the field of accessible communication.

Organisers:
María Isabel Rivas Ginel (Dublin City University)
Paolo Canavese (Université de Genève)
Patrick Cadwell (Dublin City University)
Will Noonan (Université de Bourgogne)
Martin Kappus (ZHAW School of Applied Linguistics)
Anna Matamala (Universitat Autònoma de Barcelona)
Silvia Hansen-Schirra (Johannes Gutenberg University)

Keynote: Christiane Maaß

Interactive session: Silvia Hansen-Schirra

AI & EL/LP website


3rd International Workshop on Gender-Inclusive Translation Technologies (GITT 2025)

Monday, 23 June (9 am - 5 pm)

The Gender-Inclusive Translation Technologies Workshop (GITT) is set out to be the dedicated workshop that focuses on gender-inclusive language in translation and cross-lingual scenarios. The workshop aims to bring together researchers from diverse areas, including industry partners, MT practitioners, and language professionals. GITT aims to encourage multidisciplinary research that develops and interrogates both solutions and challenges for addressing bias and promoting gender inclusivity in MT and translation tools, including LMs applications for the translation task.

Organisers:
Luisa Bentivogli (Fondazione Bruno Kessler)
Eva Vanmassenhove (Tilburg University)
Beatrice Savoldi (Fondazione Bruno Kessler)
Joke Daems (Ghent University)
Janiça Hackenbuchner (Ghent University)
Chiara Manna (Tilburg University)

GITT 2025 website gitt-workshop


3rd International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)

Tuesday, 24 June (9 am - 5 pm)

The rapid technological and methodological advances in deep learning, and in AI in general, that we see in the last decade, have not only improved machine translation, recognition of image, video and audio, the understanding of language, the synthesis of life-like 3D avatars, etc., but have also led to the fusion of interdisciplinary research that lays the foundation of automated translation services between sign and spoken languages such as the SignON and EASIER projects.
The International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL) is a one-day event aiming to bring together researchers, practitioners, interpreters and innovators who focus on SL linguistics, machine translation, natural language processing, interpreting of signed and spoken languages, image and video recognition, avatar synthesis, and other related fields, to discuss problems, challenges and opportunities for the automated and computer-assisted translation of sign-to-spoken, spoken-to-sign and sign-to-sign communication.
The third edition of AT4SSL aims to be a venue for presenting and discussing (complete, ongoing or future) research. It will feature a key-note speaker and host a discussion about current challenges, innovations and future developments related to the automatic translation between sign and spoken languages.
The theme of the third edition of the AT4SSL workshop is Co-creation for positive impact.

Organisers:
Dimitar Shterionov (Tilburg University)
Mirella De Sisto (Tilburg University)
Vincent Vandeghinste (KU Leuven & Dutch Language Institute)
Victoria Nyst (Leiden University)
Myriam Vermeerbergen (KU Leuven)
Floris Roelofsen (University of Amsterdam)
Bram Vanroy (KU Leuven & Dutch Language Institute)
Lisa Lepp (Tilburg University)
Irene Strasly (University of Geneva)

Invited speakers: Gomer Otterspeer and Tobias de Ronde.

AT4SSL 2025 website


2nd Workshop on Creative-text Translation and Technology (CTT 2025)

Tuesday, 24 June (9 am - 5 pm)

The workshop on Creative-text Translation and Technology (CTT) aims to attract a broad range of attendees, such as researchers, educators, translators and industry stakeholders, to discuss the applicability of language technology on translation efforts. Translation technology encompasses tools such as large language models (LLM), machine translation (MT) and computer-assisted translation (CAT) and their application in creative use cases such as marketing, literature and poetry, audiovisual translation and subtitling, and multilingual content creation on social media. We also encourage paper submissions on reception studies, and the development and user-testing of tools related to creative-text translation.

Organisers:
Bram Vanroy (KU Leuven & Dutch Language Institute)
Marie-Aude Lefer (UCLouvain)
Lieve Macken (Ghent University)
Paola Ruffo (University of St Andrews)
Ana Guerberof Arenas (University of Groningen)
Damien Hansen (Université libre de Bruxelles)

CTT 2025 website ctt2025


11th Workshop on Patent and Scientific Literature Translation (PSLT 2025)

Tuesday, 24 June (9 am - 12.30 pm)

Following the success of the previous workshops on Patent and Scientific Literature Translation, we are organizing the 11th Workshop on Patent and Scientific Literature Translation (PSLT 2025) held in conjunction with MT Summit 2025 in Geneva, Switzerland. The rapid growth of patent applications and scientific publications has increased the needs of machine translation for faster and larger access to technical information worldwide. Recent advances of machine translation technologies together with large-scale multilingual corpora and large language models has improved such translation significantly, while there still remain open problems to make the machine translation results more sophisticated. The workshop covers a wide range of topics related to the unique features of scientific literature including patents, scientific papers, and technical reports. The workshop, which consists of invited talks, presentation of submitted papers, and free discussion will be an opportunity for researchers and practitioners to get together and exchange their ideas and experiences.

Organisers:
Isao Goto (Ehime University)
Takashi Tsunakawa (Shizuoka University)
Katsuhito Sudoh (Nara Women’s University)

Invited speakers: Bruno Pouliquen (WIPO) and Ryota Murakami (Japan Patent Office).

PSLT 2025 website


Tutorials

The following tutorials will take place on 23-24 June.


Understanding Large Language Model-Generated Translations: How Can They Adapt to Different Translation Specifications and Pass the Translation Turing Test?

Monday, 23 June (9 am - 12.30 pm)

Want to master cutting-edge methods for evaluating LLM-generated translations? Join our interactive tutorial to learn a powerful three-pronged approach that combines the Translation Turing Test (TTT), Multidimensional Quality Metrics (MQM), and syntactic complexity analysis!
In this dynamic half-day session, you will discover how to comprehensively assess generative AI translation systems through hands-on practice. Learn to evaluate whether generative AI can truly match human project managers in translation workflows, use MQM's structured error categories to quantify translation quality, and analyze how LLMs adapt syntactic complexity based on client specifications and language pairs. Working with the CRITT TPR-DB platform, you will gain practical experience in measuring and comparing translation quality across different scenarios.
Led by experienced researchers, this tutorial is perfect for MT researchers, translation technology developers, project managers, and quality assurance specialists. You will walk away with concrete, applicable skills and a robust toolkit for evaluating and improving machine translation systems.

Join us in advancing the field of machine translation evaluation through empirically grounded methodologies and standardized assessment frameworks in this interactive learning experience!

Tutorial organisers:

Longhui Zou Dr. Longhui Zou is an assistant professor at the University of Montana, holding a Ph.D. in Translation Studies from Kent State University. Her research focuses on English-Chinese translation, LLM-assisted post-editing, and translation processes. She specializes in examining the behavioral patterns of human translators through empirical data and investigating the integration of translation technologies. Dr. Zou’s work delves into the cognitive processes and linguistic patterns in human-GenAI interactions during translation and post-editing, aiming to optimize LLM-assisted machine translation, enhance human-computer collaboration, streamline post-editing workflows, and support the long-term sustainability of human translators.
Michael Carl Dr. Michael Carl is a Distinguished Professor at Kent State University/USA and Director of the Center for Research and Innovation in Translation and Translation Technology (CRITT). He has worked and published for more than 25 years in the fields of Machine Translation, Computational Linguistics, Translation Studies and Translation Process Research. He has lived and worked in many parts of the world and organized numerous panels, tutorials, workshops, and conferences.
For more than 10 years he maintains and extends CRITT's Translation Process Research-Database (TPR-DBv), a publicly available resource that contains several hundred of hours behavioral translation data (essentially keylogging and gaze data) collected during thousands of translation sessions and hundreds of translators with different profiles, language directions and expertise. His work in the past decade was mainly centered around the conceptualization, analysis, and evaluation, as well as the empirically grounded modelling of the CRITT TPR-DB data.
Alan Melby Dr. Alan Melby has been active in the field of translation technology for over 50 years, starting in 1970, when he was a founding member of a machine translation project at Brigham Young University, where he earned an interdepartmental PhD in Computational Linguistics in 1976. Over the past five decades he has lived through all three paradigms of machine translation: rule-based, statistical, and "neural". He has not only a technical background but also a linguistic background. He is an ATA-certified French-to-English translator and taught translation theory and practice for many years. He believes that discussions of Artificial Intelligence need to go beyond software engineering and include philosophy of language. Melby's 1995 book The Possibility of Language, published by John Benjamins, does just that. More recently, he was invited to write the main chapter on machine translation for the 2019 Routledge handbook of translation and technology. His activity has not been purely academic. He served for ten years on the board of directors of the American Translators Association (ATA) and was then designated as the ATA representative to FIT (the International Federation of Translators), where he currently serves as Chair of the FIT Standards Committee, a member of the FIT Technology Committee, and Chair of the FIT North America regional center.
Brandon Torruella A recent graduate from Brigham Young University in Provo, Utah, USA, Brandon studied Linguistics with an emphasis on Language Technology. His research interests include medieval languages and computational linguistics. He also enjoys bluegrass mandolin and international cinema. He currently works as a software developer at LTAC Global developing software for translation tools and data visualization.

Leveraging Examples in Machine Translation: A Guide to Retrieval and Integration Strategies

Monday, 23 June (1.30 pm - 5 pm)

Retrieval-Augmented Generation (RAG) systems are growing popular in the era of Large Language Models (LLM). Nonetheless, retrieval augmentation has a long time story tied to Machine Translation (MT). This tutorial aims to put in perspective the various techniques used to (1) retrieve relevant examples for databases; (2) integrate them into MT models. We will uncover how the selection of examples can be performed (fuzzy matching, cross-lingual retrieval), some of the model architectures (edit-based models, augmented encoder-decoder generation models, LLMs), as well as how the augmentation affects the output. The target audience are academics and industry professionals wishing to incorporate examples to improve their translation quality.

Tutorial organisers:

Maxime Bouthors is a soon-to-be Ph.D. graduate working at ISIR - Sorbonne Université - CNRS, in collaboration with SYSTRAN by ChapsVision. His research focuses on Retrieval-Augmented Neural Machine Translation, and his thesis title is "Towards Example-Based Neural Machine Translation".
Josep Maria Crego earned his Ph.D. from the Polytechnic University of Catalonia, specializing in Statistical Machine Translation. He further pursued his work in this field as a research associate at the LIMSI-CNRS laboratory. Since 2011, he has been with SYSTRAN by ChapsVision, where he now serves as the Head of Research.

Best practices for data quality in human annotation of translation datasets

Tuesday, 24 June (1.30 pm - 5 pm)

High-quality human annotations are essential for developing and evaluating machine learning (ML) models. However, annotation is a complex task, and creating reliable annotation datasets requires addressing multiple challenges. This tutorial provides comprehensive guidance on best practices for managing data quality in human annotation of translation datasets using the Multidimensional Quality Metrics (MQM) framework. Drawing from both academic research and industry experience, we cover the complete annotation lifecycle: from initial setup and annotator management to quality evaluation and improvement strategies. Through theoretical foundations and a practical demonstration, participants will learn concrete guidelines they can apply to create more reliable and consistent annotation datasets.

Tutorial organisers:

Marina Sánchez Torrón is a Linguistic Engineer at Smartling with over 20 years of experience in the language industry, having previously worked as a translator, a computational linguist, and a language analyst. She holds a Ph.D. in Translation Studies from The University of Auckland. Her expertise and research interests revolve around translation quality, UX and AI.
Jennifer Wong has been working with Machine Learning technology since 2018, which led to her current role at Smartling where she is currently driving the AI technology research and development strategy. Her career has spanned SaaS for e-commerce, fintech, and localization, where she focused on UX, Product Management, and enterprise implementation. Jennifer has a diverse background and received her MS, Design for Interaction, Industrial Design Engineering at Delft University of Technology. Jennifer is a frequent presenter at industry conferences and webinars.