Zobrazeno 1 - 10
of 1 386
pro vyhledávání: '"Ramallo P"'
Autor:
Hosseini, Kasra, Kober, Thomas, Krapac, Josip, Vollgraf, Roland, Cheng, Weiwei, Ramallo, Ana Peleteiro
Evaluating production-level retrieval systems at scale is a crucial yet challenging task due to the limited availability of a large pool of well-trained human annotators. Large Language Models (LLMs) have the potential to address this scaling issue a
Externí odkaz:
http://arxiv.org/abs/2409.11860
Autor:
Celikik, Marjan, Wasilewski, Jacek, Ramallo, Ana Peleteiro, Kurennoy, Alexey, Labzin, Evgeny, Ascione, Danilo, Gurbanov, Tural, Falher, Géraud Le, Dzhoha, Andrii, Harris, Ian
Modern e-commerce platforms offer vast product selections, making it difficult for customers to find items that they like and that are relevant to their current session intent. This is why it is key for e-commerce platforms to have near real-time sca
Externí odkaz:
http://arxiv.org/abs/2409.02856
Large language models (LLMs) are poised to revolutionize the domain of online fashion retail, enhancing customer experience and discovery of fashion online. LLM-powered conversational agents introduce a new way of discovery by directly interacting wi
Externí odkaz:
http://arxiv.org/abs/2408.08907
Autor:
Matteucci, Federico, Arzamasov, Vadim, Cribeiro-Ramallo, Jose, Heyden, Marco, Ntounas, Konstantin, Böhm, Klemens
Experimental studies are a cornerstone of machine learning (ML) research. A common, but often implicit, assumption is that the results of a study will generalize beyond the study itself, e.g. to new data. That is, there is a high probability that rep
Externí odkaz:
http://arxiv.org/abs/2406.17374
Large-scale randomised experiments have become a standard tool for developing products and improving user experience. To reduce losses from shipping harmful changes experimental results are, in practice, often checked repeatedly, which leads to infla
Externí odkaz:
http://arxiv.org/abs/2406.16523
Outlier detection in high-dimensional tabular data is an important task in data mining, essential for many downstream tasks and applications. Existing unsupervised outlier detection algorithms face one or more problems, including inlier assumption (I
Externí odkaz:
http://arxiv.org/abs/2404.14451
We study the non-equilibrium dynamics of two coupled SYK models, conjectured to be holographically dual to an eternal traversable wormhole in AdS$_2$. We consider different periodic drivings of the parameters of the system. We analyze the energy flow
Externí odkaz:
http://arxiv.org/abs/2404.08394
Outlier generation is a popular technique used for solving important outlier detection tasks. Generating outliers with realistic behavior is challenging. Popular existing methods tend to disregard the 'multiple views' property of outliers in high-dim
Externí odkaz:
http://arxiv.org/abs/2402.03846
Autor:
Zaugg, Serge, van der Schaar, Mike, Erbs, Florence, Sanchez, Antonio, Castell, Joan V., Ramallo, Emiliano, André, Michel
Automated classification of animal sounds is a prerequisite for large-scale monitoring of biodiversity. Convolutional Neural Networks (CNNs) are among the most promising algorithms but they are slow, often achieve poor classification in the field and
Externí odkaz:
http://arxiv.org/abs/2312.03666
Autor:
Dibak, Manuel, Vlasov, Vladimir, Karessli, Nour, Dedik, Darya, Malykh, Egor, Wasilewski, Jacek, Torres, Ton, Ramallo, Ana Peleteiro
Data-driven personalization is a key practice in fashion e-commerce, improving the way businesses serve their consumers needs with more relevant content. While hyper-personalization offers highly targeted experiences to each consumer, it requires a s
Externí odkaz:
http://arxiv.org/abs/2309.13068