MEANING

May 30, 2002 | Projects

- PROJECT CLOSED

MEANING will be concerned with automatically collecting and analysing language data from the WWW on a large scale, and building more comprehensive multilingual lexical knowledge bases to support improved word sense disambiguation (WSD). Current web access applications are based on words; MEANING will open the way for access to the Multilingual Web based on concepts, providing applications with capabilities that significantly exceed those currently available. MEANING will facilitate development of concept-based open domain Internet applications (such as Question/Answering, Cross Lingual Information Retrieval, Summarisation, Text Categorisation, Event Tracking, Information Extraction, Machine Translation, etc.). Furthermore, MEANING will supply a common conceptual structure to Internet documents, thus facilitating knowledge management of web content.

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#MachineTranslation Research Unit @FBK_research. #nlproc #deeplearning #ai

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MT Group at FBK

@fbk_mt ·

21 Oct

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.

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MT Group at FBK

@fbk_mt ·

15 Oct

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.

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MT Group at FBK

@fbk_mt ·

7 Oct

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?

Marco Gaido @mgaido91

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

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@fbk_mt ·

21 Sep

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.

BeatriceSavoldi @BeatriceSavoldi

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

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