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.
The 22nd edition of IWSLT will be co-located with @aclmeeting in Vienna, Austria on 31 July-1 Aug 2025!
Stay tuned for the CFP and more info about our 2025 shared tasks! Join our google group for periodic updates.
In "Twists, Humps, and Pebbles: Multilingual Speech Recognition Models Exhibit Gender Performance Gaps," @BeatriceSavoldi, @DennisFucci, @dirk_hovy, and I show how speech recognition serves different gender groups differently and what to do about it.
Meet @sarapapi, @BeatriceSavoldi, and @negri_teo at EMNLP 2024 in Miami next week! 🌴
They will present two main conference papers about human-centered #MT and #genderbias, and #opensource #speech resources!
📍 Details here: https://mt.fbk.eu/our-postdocs-sara-papi-and-beatrice-savoldi-and-our-researcher-matteo-negri-at-emnlp-2024/
#NLProc #EMNLP2024
Weekly pick from the #MeetweenScientificWatch: "Vcoder: Versatile Vision Encoders for Multimodal LLMs" - A novel encoder boosts object perception in MLLMs, outperforming GPT-4V in visual reasoning! 🌆👀