Zobrazeno 1 - 10
of 2 425
pro vyhledávání: '"Brutti, A."'
Autor:
Santos, Diogo Reis, Protani, Andrea, Giusti, Lorenzo, Aillet, Albert Sund, Brutti, Pierpaolo, Serio, Luigi
Early detection of atrial fibrillation (AFib) is challenging due to its asymptomatic and paroxysmal nature. However, advances in deep learning algorithms and the vast collection of electrocardiogram (ECG) data from devices such as the Internet of Thi
Externí odkaz:
http://arxiv.org/abs/2410.19781
MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages
Autor:
Gaido, Marco, Papi, Sara, Bentivogli, Luisa, Brutti, Alessio, Cettolo, Mauro, Gretter, Roberto, Matassoni, Marco, Nabih, Mohamed, Negri, Matteo
The rise of foundation models (FMs), coupled with regulatory efforts addressing their risks and impacts, has sparked significant interest in open-source models. However, existing speech FMs (SFMs) fall short of full compliance with the open-source pr
Externí odkaz:
http://arxiv.org/abs/2410.01036
Autor:
Protani, Andrea, Giusti, Lorenzo, Iacovelli, Chiara, Aillet, Albert Sund, Santos, Diogo Reis, Reale, Giuseppe, Zauli, Aurelia, Moci, Marco, Garbuglia, Marta, Brutti, Pierpaolo, Caliandro, Pietro, Serio, Luigi
After an acute stroke, accurately estimating stroke severity is crucial for healthcare professionals to effectively manage patient's treatment. Graph theory methods have shown that brain connectivity undergoes frequency-dependent reorganization post-
Externí odkaz:
http://arxiv.org/abs/2410.07199
Autor:
Cappellazzo, Umberto, Kim, Minsu, Chen, Honglie, Ma, Pingchuan, Petridis, Stavros, Falavigna, Daniele, Brutti, Alessio, Pantic, Maja
Multimodal large language models (MLLMs) have recently become a focal point of research due to their formidable multimodal understanding capabilities. For example, in the audio and speech domains, an LLM can be equipped with (automatic) speech recogn
Externí odkaz:
http://arxiv.org/abs/2409.12319
Automatic speech recognition models require large amounts of speech recordings for training. However, the collection of such data often is cumbersome and leads to privacy concerns. Federated learning has been widely used as an effective decentralized
Externí odkaz:
http://arxiv.org/abs/2405.17376
Publikováno v:
SemEval-2024
We present a baseline for the SemEval 2024 task 2 challenge, whose objective is to ascertain the inference relationship between pairs of clinical trial report sections and statements. We apply prompt optimization techniques with LLM Instruct models p
Externí odkaz:
http://arxiv.org/abs/2405.01942
Persistent homology (PH) is a powerful mathematical method to automatically extract relevant insights from images, such as those obtained by high-resolution imaging devices like electron microscopes or new-generation telescopes. However, the applicat
Externí odkaz:
http://arxiv.org/abs/2404.08245
Autor:
Khebour, Ibrahim, Lai, Kenneth, Bradford, Mariah, Zhu, Yifan, Brutti, Richard, Tam, Christopher, Tu, Jingxuan, Ibarra, Benjamin, Blanchard, Nathaniel, Krishnaswamy, Nikhil, Pustejovsky, James
Within Dialogue Modeling research in AI and NLP, considerable attention has been spent on ``dialogue state tracking'' (DST), which is the ability to update the representations of the speaker's needs at each turn in the dialogue by taking into account
Externí odkaz:
http://arxiv.org/abs/2403.17284
Mixture of Experts (MoE) architectures have recently started burgeoning due to their ability to scale model's capacity while maintaining the computational cost affordable. Furthermore, they can be applied to both Transformers and State Space Models,
Externí odkaz:
http://arxiv.org/abs/2402.00828
Parameter-efficient transfer learning (PETL) methods have emerged as a solid alternative to the standard full fine-tuning approach. They only train a few extra parameters for each downstream task, without sacrificing performance and dispensing with t
Externí odkaz:
http://arxiv.org/abs/2312.03694