Tasks that ultimately require knowledge-based multimedia techniques (content-oriented search, assessment, abstracting, etc.) are still to a major extent carried out manually. PATExpert’s overall scientific goal is to change the paradigm currently followed for patent processing from textual (viewing patents as text blocks enriched by “canned” picture material, sequences of morpho-syntactic tokens, or collections of syntactic structures) to semantic (viewing patents as multimedia knowledge objects) processing. PATExpert developed a multimedia content representation formalism based on Semantic Web technologies for selected technology areas and investigate the retrieval, classification, multilingual generation of concise patent information, assessment and visualization of patent material encoded in this formalism, taking the information needs of all user types as defined in a user typology into account. PATExpert’s technological goal was to develop a showcase that demonstrates the viability of PATExpert’s approach to content representation for real applications. The composition and the competence of the Consortium ensured the achievement of these goals.
SHADES: a global dataset to uncover AI bias
Over 50 researchers, 16 languages, thousands of interactions analysed: the international SHADES project investigates how generative language models (LLM) reproduce and amplify cultural stereotypes
◾https://magazine.fbk.eu/en/news/shades-the-new-global-dataset-to-monitor-as-ai-reproduces-and-invents-cultural-stereotypes/
🎉 Excited to share our paper “Different Speech Translation Models Encode and Translate Speaker Gender Differently” was accepted at #ACL2025 (main)!
✍🏼 Big thanks to amazing co-authors: @mgaido91, @negri_teo, @luisabentivogli, @andre_t_martins, @peppeatta!
📄 Preprint out soon!
🎉 Excited to share that our @sarapapi has won the 2024 Best PhD Award from the Information and Engineering Doctoral School at @UniTrento_DISI for her thesis “Direct Speech Translation in Constrained Contexts: The Simultaneous and Subtitling Scenarios.”
#nlproc @FBK_research
🎉 Excited to share that our @sarapapi has won the 2024 Best PhD Award from the Information and Engineering Doctoral School at @UniTrento_DISI for her thesis “Direct Speech Translation in Constrained Contexts: The Simultaneous and Subtitling Scenarios.”
#nlproc @FBK_research