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.
Our #PickOfTheWeek 📚: “High-Fidelity Simultaneous Speech-To-Speech Translation” by @t0m1ab, @lmazare, @EXGRV, @ptrkprz, @honualx and @neilzegh
🎙️➡️🌍 This work shows how a full-duplex SpeechLLM architecture can be adapted for simultaneous S2ST and S2TT.
Can LLM Agents Learn how to behave According to your preferences?
PersonaAgent is a framework that combines personalized memory and tool use to help LLM agents adapt their actions to individual users without fine-tuning the underlying model.
Our #PickOfTheWeek, selected by @mgaido91: "Alignment Is All You Need: Instruction-Free Training for General Audio-Language Models" by Xuanru Zhou, Yiwen Shao, Jiahong Li, and Dong Yu 🎧
Can instruction-free training power the next generation of audio-language models?
Cool to see we are not the only ones working on building SpeechLLMs with instruction-following capabilities without requiring LLM adaptation and instruction-following data that is expensive to collect!
https://arxiv.org/abs/2608.18132
@fbk_mt
Our #PickOfTheWeek, selected by @BeatriceSavoldi:
"The AI Observatory: A Public Measure of Real-World AI Use" by @ShayneRedford, @AnkaReuel, @zoeykii et al.
A crucial framework tracking how AI models are deployed, adopted, and evaluated beyond lab benchmarks.
Pick of the week @fbk_mt
📚"The AI Observatory: A Public Measure of Real-World AI Use"
A study and taxonomy to explore real conversations across multiple datasets.
https://www.dataprovenance.org/ai_observatory.pdf