TOSCA-MP

Oct 1, 2011 | Projects

1 October 2011 to 31 March 2014 - PROJECT CLOSED

The TOSCA-MP project aimed to develop user-centric content annotation and search tools for professionals in networked media production and archiving (television, radio, online), addressing their specific use cases and workflow requirements. The project brought together 10 partners from 6 European countries including industry partners providing solutions for the media industry, public service broadcasters as well as their European association, a university and research centres. TOSCA-MP investigated scalable and distributed content processing methods performing advanced multimodal information extraction and semantic enrichment. Other key technology areas included search methods across heterogeneous networked content repositories and novel user interfaces. An open standards based service oriented framework integrated the components of the system.

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

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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

@fbk_mt

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MT Group at FBK

@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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MT Group at FBK

@fbk_mt ·

9 Sep

Can algorithmic gender prediction ever be valid?

Check out this week's top pick by @lina_conti: "Algorithmic Gender Prediction Is Illegitimate, But Gender Imputation Can Yield Valid Measurements" by @evandongyx & @ang3linawang.

Lina Conti @lina_conti

Pick of the week by @evandongyx & @ang3linawang:
https://arxiv.org/pdf/2608.13444

Predicting gender from images or names can reveal discrimination. But the practice itself harms trans people. This paper works through when that tradeoff might be justified and how to do it responsibly.

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MT Group at FBK

@fbk_mt ·

3 Sep

Our pick of the week by
@dhairya_su47605
: "Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression" by @hanqi_xiao, @yilin_sung, @EliasEskin and @mohitban47
#Quantization #Interpretibility

Dhairya Suman @dhairya_su47605

#PickoftheWeek @fbk_mt
Super cool paper on leavaraging Interpretability for Compression!

https://arxiv.org/pdf/2504.07389

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