Zobrazeno 1 - 10
of 3 140
pro vyhledávání: '"Á. Barahona"'
Publikováno v:
COLING 2025 Workshop on Detecting AI Generated Content, Jan 2025, Abu dahbi, United Arab Emirates
Detecting synthetic tabular data is essential to prevent the distribution of false or manipulated datasets that could compromise data-driven decision-making. This study explores whether synthetic tabular data can be reliably identified ''in the wild'
Externí odkaz:
http://arxiv.org/abs/2412.13227
Autor:
Elizabeth, Michelle, Veyret, Morgan, Couceiro, Miguel, Dusek, Ondrej, Rojas-Barahona, Lina M.
Large language models (LLMs) gained immense popularity due to their impressive capabilities in unstructured conversations. However, they underperform compared to previous approaches in task-oriented dialogue (TOD), wherein reasoning and accessing ext
Externí odkaz:
http://arxiv.org/abs/2412.01262
Autor:
Barahona, Sara, Mošner, Ladislav, Stafylakis, Themos, Plchot, Oldřich, Peng, Junyi, Burget, Lukáš, Černocký, Jan
In this paper, we refine and validate our method for training speaker embedding extractors using weak annotations. More specifically, we use only the audio stream of the source VoxCeleb videos and the names of the celebrities without knowing the time
Externí odkaz:
http://arxiv.org/abs/2410.02364
The high binding affinity of antibodies towards their cognate targets is key to eliciting effective immune responses, as well as to the use of antibodies as research and therapeutic tools. Here, we propose ANTIPASTI, a Convolutional Neural Network mo
Externí odkaz:
http://arxiv.org/abs/2410.01523
Publikováno v:
ESPOCH Congresses, Vol 1, Iss 4, Pp 1155-1165 (2021)
Abstract The present investigation proposes to determine the form factor of the species Eucalyptus saligna in a commercial forest plantation of the Tambillo bajo sector, of the Colta canton, Chimborazo province. For this purpose, 100 individual speci
Externí odkaz:
https://doaj.org/article/138720137ef24570bc3d71af52e99adf
Traditional models based solely on pairwise associations often fail to capture the complex statistical structure of multivariate data. Existing approaches for identifying information shared among groups of $d>3$ variables are frequently computational
Externí odkaz:
http://arxiv.org/abs/2408.07533
Autor:
Rojpaisarnkit, Ruksit, Robles, Gregorio, Kula, Raula Gaikovina, Wang, Dong, Ragkhitwetsagul, Chaiyong, Gonzalez-Barahona, Jesus M., Matsumoto, Kenichi
Python, one of the most prevalent programming languages today, is widely utilized in various domains, including web development, data science, machine learning, and DevOps. Recent scholarly efforts have proposed a methodology to assess Python compete
Externí odkaz:
http://arxiv.org/abs/2408.02262
Autor:
Ng, Wai Kit, Dranczewski, Jakub, Fischer, Anna, Raziman, T V, Saxena, Dhruv, Farchy, Tobias, Stenning, Kilian, Peters, Jonathan, Schmid, Heinz, Branford, Will R, Barahona, Mauricio, Moselund, Kirsten, Sapienza, Riccardo, Gartside, Jack C.
With the growing prevalence of AI, demand increases for efficient machine learning hardware. Physical systems are sought which combine image feature detection with the essential nonlinearity for tasks such as image classification. Existing physical h
Externí odkaz:
http://arxiv.org/abs/2407.15558
Autor:
Raziman, T. V., Fischer, Anna, Nori, Riccardo, Chan, Anthony, Ng, Wai Kit, Saxena, Dhruv, Hess, Ortwin, Molkens, Korneel, Tanghe, Ivo, Geiregat, Pieter, Van Thourhout, Dries, Barahona, Mauricio, Sapienza, Riccardo
Near-field coupling between nanolasers enables collective high-power lasing but leads to complex spectral reshaping and multimode operation, limiting the emission brightness, spatial coherence and temporal stability. Many lasing architectures have be
Externí odkaz:
http://arxiv.org/abs/2407.04062
Autor:
Ng, Wai Kit, Raziman, T. V., Saxena, Dhruv, Molkens, Korneel, Tanghe, Ivo, Xuan, Zhenghe, Geiregat, Pieter, Van Thourhout, Dries, Barahona, Mauricio, Sapienza, Riccardo
Understanding the behaviour of complex laser systems is an outstanding challenge, especially in the presence of nonlinear interactions between modes. Hidden features, such as the gain distributions and spatial localisation of lasing modes, often cann
Externí odkaz:
http://arxiv.org/abs/2407.03815