Luisa Bentivogli at Interspeech2026 in Sydney ๐ฆ๐บ
Three papers co-authored by researchers from the MT Unit were presented at Interspeech 2026, the...
Read Moreby Luca Corbucci | Oct 13, 2026 | News, Uncategorized | 0
Three papers co-authored by researchers from the MT Unit were presented at Interspeech 2026, the...
Read Moreby Luca Corbucci | Aug 5, 2026 | News, Uncategorized | 0
We are happy to announce that 3 papers, co-authored by our Machine Translation Group, have been...
Read Moreby Luca Corbucci | Jul 1, 2026 | News, Uncategorized | 0
The Machine Translation unit is heading to the ACL 2026 Conference in San Diego, California! Luisa...
Read Moreby Luca Corbucci | Jun 11, 2026 | News, Uncategorized | 0
Weโre glad to share that the three papers, co-authored by our Machine Translation Group at FBK,...
Read Moreby Luca Corbucci | May 11, 2026 | News, Uncategorized | 0
The MT Unit is heading to LREC 2026 in Palma de Mallorca (May 11โ16)! Lina Conti and Luisa...
Read Moreby Luca Corbucci | Apr 22, 2026 | News, Uncategorized | 0
We are happy to announce that Sara Papi is attending ICLR 2026 in Rio de Janeiro, Brazil ๐ง๐ท. She...
Read Moreby admin | May 10, 2023 | Uncategorized | 0
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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 ๐ง
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
๐"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
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.
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.