**** We apologize for the multiple copies of this email. In case you are already registered to the next webinar, you do not need to register again. **** Dear colleague,
We are happy to announce the next webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). We are organizing one seminar every month.
Next webinar:
Speaker: Ivan Vulić (University of Cambridge / Google DeepMind) Title: On Merging and MoErging Models and Modules Date: Thursday, November 6, 2025 - 15:00 CET
Summary: Despite recent tendencies towards building large "monolithic" neural models, fine-tuned expert models and parameter-efficient specialised modules still offer gains over large monoliths in specific tasks and for specific data distributions (e.g., low-resource languages or specialised domains). Moreover, such modularisation of skills and expertise into dedicated models or modules allows for asynchronous, decentralised, and more efficient continuous model development, as well as module reusability. However, a central question remains: how to combine and compose these modules to enable positive transfer, sample-efficient learning, and improved out-of-domain generalisation. In this talk, after discussing the key advantages of modularisation and modular specialisation, I will provide an overview of prominent module and model composition strategies. I will focus on composition at the parameter level (model merging) and functional level (model MoErging), and then illustrate the usefulness of these techniques across several applications.
Bio: Ivan Vulić is currently a Research Scientist at Google DeepMind in Zurich after spending a year there as a Visiting Researcher. Before that he was a Research Professor and a Royal Society University Research Fellow in the Language Technology Lab, University of Cambridge, where he spent 10 years across different research roles. From January 2018 until November 2024 he was also a Senior Scientist at PolyAI in London. Ivan holds a PhD in Computer Science from KU Leuven awarded summa cum laude. In 2021 he was awarded the annual Karen Spärck Jones Award from the British Computing Society for his research contributions to Natural Language Processing and Information Retrieval. His core expertise and research interests span, among others, cross-lingual, multilingual and multi-modal representation learning, modularity and composability of ML models, sample-efficient, parameter-efficient and few-shot ML, conversational AI, data-centric ML.
Registration: https://www.hitz.eus/webinar_izenematea
You can view the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars
Upcoming webinars:
Goran Glavaš (December 4) Thamar Solorio (January 15) Henning Wachsmuth (February 5)
Check past and upcoming webinars at the following url: http://www.hitz.eus/webinars If you are interested in participating, please complete this registration form: http://www.hitz.eus/webinar_izenematea
If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info
Best wishes,
HiTZ Zentroa
P.S: HiTZ will not grant any type of certificate for attendance at these webinars.