Zobrazeno 1 - 10
of 6 407
pro vyhledávání: '"Viegas P"'
PATopics: An automatic framework to extract useful information from pharmaceutical patents documents
Autor:
Cecilio, Pablo, Perreira, Antônio, Viegas, Juliana Santos Rosa, Cunha, Washington, Viegas, Felipe, Tuler, Elisa, Vicentini, Fabiana Testa Moura de Carvalho, Rocha, Leonardo
Pharmaceutical patents play an important role by protecting the innovation from copies but also drive researchers to innovate, create new products, and promote disruptive innovations focusing on collective health. The study of patent management usual
Externí odkaz:
http://arxiv.org/abs/2408.08905
According to Eurostat estimates, the overall number of farms in Europe declined of about 3 million units between 2010 and 2020. Parallel, the agricultural standard output increased from 304 billion to nearly 360 billion over the same period. Such evi
Externí odkaz:
http://arxiv.org/abs/2409.00111
Sign Language Recognition has been studied and developed throughout the years to help the deaf and hard-of-hearing people in their day-to-day lives. These technologies leverage manual sign recognition algorithms, however, most of them lack the recogn
Externí odkaz:
http://arxiv.org/abs/2407.15668
Many neural nets appear to represent data as linear combinations of "feature vectors." Algorithms for discovering these vectors have seen impressive recent success. However, we argue that this success is incomplete without an understanding of relatio
Externí odkaz:
http://arxiv.org/abs/2407.14662
Dialogue Action Tokens: Steering Language Models in Goal-Directed Dialogue with a Multi-Turn Planner
We present an approach called Dialogue Action Tokens (DAT) that adapts language model agents to plan goal-directed dialogues. The core idea is to treat each utterance as an action, thereby converting dialogues into games where existing approaches suc
Externí odkaz:
http://arxiv.org/abs/2406.11978
Autor:
Chen, Yida, Wu, Aoyu, DePodesta, Trevor, Yeh, Catherine, Li, Kenneth, Marin, Nicholas Castillo, Patel, Oam, Riecke, Jan, Raval, Shivam, Seow, Olivia, Wattenberg, Martin, Viégas, Fernanda
Conversational LLMs function as black box systems, leaving users guessing about why they see the output they do. This lack of transparency is potentially problematic, especially given concerns around bias and truthfulness. To address this issue, we p
Externí odkaz:
http://arxiv.org/abs/2406.07882
Olfaction sensing in autonomous robotics faces challenges in dynamic operations, energy efficiency, and edge processing. It necessitates a machine learning algorithm capable of managing real-world odor interference, ensuring resource efficiency for m
Externí odkaz:
http://arxiv.org/abs/2407.04714
This paper presents TE-NeXt, a novel and efficient architecture for Traversability Estimation (TE) from sparse LiDAR point clouds based on a residual convolution block. TE-NeXt block fuses notions of current trends such as attention mechanisms and 3D
Externí odkaz:
http://arxiv.org/abs/2406.01395
Microbial assessment in a rare Norwegian book collection: a One Health approach to cultural heritage
Autor:
Sequeira, Sílvia O., Pasnak, Ekaterina, Viegas, Carla, Gomes, Bianca, Dias, Marta, Cervantes, Renata, Pena, Pedro, Twarużek, Magdalena, Kosicki, Robert, Viegas, Susana, Caetano, Liliana Aranha, Penetra, Maria João, Santos, Inês, Caldeira, Ana Teresa, Pinheiro, Catarina
Microbial contamination poses a threat to both the preservation of library and archival collections and the health of staff and users. This study investigated the microbial communities and potential health risks associated with the UNESCO-classified
Externí odkaz:
http://arxiv.org/abs/2404.00110
This paper presents MinkUNeXt, an effective and efficient architecture for place-recognition from point clouds entirely based on the new 3D MinkNeXt Block, a residual block composed of 3D sparse convolutions that follows the philosophy established by
Externí odkaz:
http://arxiv.org/abs/2403.07593