Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices.
Cosa chiedono davvero gli italiani all’intelligenza artificiale?
FBK in collaborazione con RiTA lancia un’indagine aperta a tutte/i per capire usi reali, abitudini e bisogni.
Bastano 10 minuti per partecipare, scopri di più: https://magazine.fbk.eu/it/news/italiani-e-ia-cosa-chiediamo-veramente-allintelligenza-artificiale/
🚀 Last call for the Model Compression for Machine Translation task at #WMT2025 (co-located with #EMNLP2025)!
Test data out on June 19 ➡️ 2 weeks for evaluation!
Can you shrink an LLM and keep translation quality high?
👉 https://www2.statmt.org/wmt25/model-compression.html #NLP #ML #LLM #ModelCompression
Our pick of the week by @beomseok_lee_: "ALAS: Measuring Latent Speech-Text Alignment For Spoken Language Understanding In Multimodal LLMs" by Pooneh Mousavi, @yingzhi_wang, @mirco_ravanelli, and @CemSubakan (2025)
#SLU #speech #multimodal #LLM
Speech-language models show promise in multimodal tasks—but how well are speech & text actually aligned? 🤔
This paper https://arxiv.org/abs/2505.19937 proposes a new metric to measure layer-wise correlation between the two, with a focus on SLU tasks. 🔍🗣️📄
🔍 Ciao! Stiamo studiando come l'AI viene usata in Italia e per farlo abbiamo costruito un sondaggio!
👉https://bocconi.eu.qualtrics.com/jfe/form/SV_2nTelXaXvJlinbg (è anonimo, dura ~10 m, se partecipi o lo diffondi ci aiuti un sacco🙏)
Ci interessa anche raggiungere persone che non si occupano di AI!