The FACILE project aimed at the development of a system for the categorisation of texts from the area of finance and business news in an exact and specific way. The intended users of the system were institutions from finance and commerce that have a vital interest in up-to-date business information stemming from online news agencies and periodicals. An important consideration in FACILE has been its use across country and language borders. The possibility to process texts in various languages and to derive factual information in a language independent, formatted form allowed for the rapid dissemination of information across borders.
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