The combination of dynamic user-generated content and multilingual aspects is particularly prominent in Wiki sites. Wikis have gained increased popularity over the last few years as a means of collaborative content creation as they allow users to set up and edit web pages directly. A growing number of organizations use Wikis as an efficient means to provide and maintain information across several sites. Currently, multilingual Wikis rely on users to manually translate different Wiki pages on the same subject. This is not only a time-consuming procedure but also the source of many inconsistencies, as users update the different language versions separately, and every update would require translators to compare the different language versions and synchronize the updates. The overall aim of the CoSyne project is to automate the dynamic multilingual synchronization process of Wikis.
Emanuele Pianta Award for the Best Master’s Thesis in Computational Linguistics submitted at an Italian university and defended between August 1st 2024 and July 31st 2025
- Deadline: August 1st, 2025 (11:59 pm CEST)
- All details online: https://clic2025.unica.it/emanuele-pianta-award-for-the-best-masters-thesis/
Our pick of the week by @DennisFucci: "Speech Representation Analysis Based on Inter- and Intra-Model Similarities" by Yassine El Kheir, Ahmed Ali, and Shammur Absar Chowdhury (ICASSP Workshops 2024)
#speech #speechtech
Findings from https://ieeexplore.ieee.org/document/10669908 show that speech SSL models converge on similar embedding spaces, but via different routes. While overall representations align, individual neurons learn distinct localized concepts.
Interesting read! @fbk_mt
Cosa chiedono davvero gli italiani all’intelligenza artificiale?
FBK in collaborazione con RiTA lancia un’indagine aperta a tutte/i per capire usi reali, abitudini e bisogni.
Bastano 10 minuti per partecipare, scopri di più: https://magazine.fbk.eu/it/news/italiani-e-ia-cosa-chiediamo-veramente-allintelligenza-artificiale/
🚀 Last call for the Model Compression for Machine Translation task at #WMT2025 (co-located with #EMNLP2025)!
Test data out on June 19 ➡️ 2 weeks for evaluation!
Can you shrink an LLM and keep translation quality high?
👉 https://www2.statmt.org/wmt25/model-compression.html #NLP #ML #LLM #ModelCompression