JUMAS addresses the need to build an infrastructure able to optimise the information workflow in order to facilitate later analysis. New models and techniques for representing and automatically extracting the embedded semantics derived from multiple data sources will be developed. The most important goal of the JUMAS system is to collect, enrich and share multimedia documents annotated with embedded semantic minimising manual transcription activity. JUMAS is tailored at managing situations in which multiple cameras and audio sources are used to record assemblies in which people debates and event sequences need to be semantically reconstructed for future consultations. The prototype of JUMAS will be tested interworking with legacy systems, but the system can be viewed as able to support business processes and problem-solving in a variety of domains.
1 January 2009 to 31 March 2011 - PROJECT CLOSED
🚀 New Shared Task: Model Compression for Machine Translation at #WMT2026 (co-located with #EMNLP2026)!
📅 Test data out on June 18th, submissions by July 2nd!
Can you shrink an LLM and keep translation quality high? 🧠🔧
👉 https://www2.statmt.org/wmt26/model-compression.html #NLP #ML #LLM #ModelCompression
With @MalvinaNissim and @VivianaPatti, we've been teaching ethics in NLP as a hands-on course across Groningen, Pavia & Turin. We wrote up the experience and received the ✨Best Paper Award✨ at #EACL2026's TeachNLP Workshop. Huge thanks to the organizers and all our students!