Zobrazeno 1 - 10
of 2 508
pro vyhledávání: '"Labonne, A."'
Merging in a Bottle: Differentiable Adaptive Merging (DAM) and the Path from Averaging to Automation
Autor:
Gauthier-Caron, Thomas, Siriwardhana, Shamane, Stein, Elliot, Ehghaghi, Malikeh, Goddard, Charles, McQuade, Mark, Solawetz, Jacob, Labonne, Maxime
By merging models, AI systems can combine the distinct strengths of separate language models, achieving a balance between multiple capabilities without requiring substantial retraining. However, the integration process can be intricate due to differe
Externí odkaz:
http://arxiv.org/abs/2410.08371
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-5 (2024)
Large language models (LLMs) are increasingly applied in medical documentation and have been proposed for clinical decision support. We argue that the future for LLMs in medicine must be based on transparent and controllable open-source models. Openn
Externí odkaz:
https://doaj.org/article/363c9719182e41729d9d40676a541c47
Autor:
Gourgoulias, Kostis, Ghalyan, Najah, Labonne, Maxime, Satsangi, Yash, Moran, Sean, Sabelja, Joseph
This paper introduces an unsupervised method to estimate the class separability of text datasets from a topological point of view. Using persistent homology, we demonstrate how tracking the evolution of embedding manifolds during training can inform
Externí odkaz:
http://arxiv.org/abs/2305.15016
Autor:
Labonne, Maxime, Moran, Sean
This paper investigates the effectiveness of large language models (LLMs) in email spam detection by comparing prominent models from three distinct families: BERT-like, Sentence Transformers, and Seq2Seq. Additionally, we examine well-established mac
Externí odkaz:
http://arxiv.org/abs/2304.01238
Autor:
Labonne, Paul
Publikováno v:
In International Journal of Forecasting January-March 2025 41(1):229-250
Autor:
Cavailles, Julie, Vaca-Medina, Guadalupe, Wu-Tiu-Yen, Jenny, Labonne, Laurent, Evon, Philippe, Peydecastaing, Jérôme, Pontalier, Pierre-Yves
Publikováno v:
In Bioresource Technology December 2024 414
Predicting the bandwidth utilization on network links can be extremely useful for detecting congestion in order to correct them before they occur. In this paper, we present a solution to predict the bandwidth utilization between different network lin
Externí odkaz:
http://arxiv.org/abs/2112.02417
In order to properly train a machine learning model, data must be properly collected. To guarantee a proper data collection, verifying that the collected data set holds certain properties is a possible solution. For example, guaranteeing that the dat
Externí odkaz:
http://arxiv.org/abs/2108.11220
Autor:
María del Pilar Meza-Rodríguez, Blanca Farfan-Labonne, Miroslava Avila-García, Ricardo Figueroa-Damian, Noemí Plazola-Camacho, Gabriela Pellón-Díaz, Braulio Alfonso Ríos-Flores, Efraín Olivas-Peña, Phillipe Leff-Gelman, Ignacio Camacho-Arroyo
Publikováno v:
BMC Psychology, Vol 11, Iss 1, Pp 1-8 (2023)
Abstract Purpose To evaluate the presence of psychological distress (PD) and its association with the mental health and coping styles of pregnant women living with HIV (PWLWH). Method An observational, cross-sectional descriptive study was performed.
Externí odkaz:
https://doaj.org/article/4a77ecad0e6342e7aa6391e2b3d3cf4b
Publikováno v:
In Industrial Crops & Products April 2024 210