Zobrazeno 1 - 10
of 5 450
pro vyhledávání: '"González, P. E."'
This project, named HEnRY, aims to introduce a Multi-Agent System (MAS) into Intesa Sanpaolo. The name HEnRY summarizes the project's core principles: the Hierarchical organization of agents in a layered structure for efficient resource management; E
Externí odkaz:
http://arxiv.org/abs/2410.12720
Generating diverse responses from large language models (LLMs) is crucial for applications such as planning/search and synthetic data generation, where diversity provides distinct answers across generations. Prior approaches rely on increasing temper
Externí odkaz:
http://arxiv.org/abs/2410.09038
Autor:
Yang, Ling, Yu, Zhaochen, Zhang, Tianjun, Xu, Minkai, Gonzalez, Joseph E., Cui, Bin, Yan, Shuicheng
Large language models (LLMs) like GPT-4, PaLM, and LLaMA have shown significant improvements in various reasoning tasks. However, smaller models such as Llama-3-8B and DeepSeekMath-Base still struggle with complex mathematical reasoning because they
Externí odkaz:
http://arxiv.org/abs/2410.09008
Large language models (LLMs) often exhibit subtle yet distinctive characteristics in their outputs that users intuitively recognize, but struggle to quantify. These "vibes" - such as tone, formatting, or writing style - influence user preferences, ye
Externí odkaz:
http://arxiv.org/abs/2410.12851
We investigate the mechanical behavior of jammed knitted fabrics, where geometric confinement leads to an initially stiff mechanical response that softens into low stiffness behavior with additional applied stress. We show that the jammed regime is d
Externí odkaz:
http://arxiv.org/abs/2410.03940
The Automated Audio Captioning (AAC) task asks models to generate natural language descriptions of an audio input. Evaluating these machine-generated audio captions is a complex task that requires considering diverse factors, among them, auditory sce
Externí odkaz:
http://arxiv.org/abs/2409.12962
Autor:
Biswal, Asim, Patel, Liana, Jha, Siddarth, Kamsetty, Amog, Liu, Shu, Gonzalez, Joseph E., Guestrin, Carlos, Zaharia, Matei
AI systems that serve natural language questions over databases promise to unlock tremendous value. Such systems would allow users to leverage the powerful reasoning and knowledge capabilities of language models (LMs) alongside the scalable computati
Externí odkaz:
http://arxiv.org/abs/2408.14717
The inference process for large language models is slow and memory-intensive, with one of the most critical bottlenecks being excessive Key-Value (KV) cache accesses. This paper introduces "Double Sparsity," a novel post-training sparse attention tec
Externí odkaz:
http://arxiv.org/abs/2408.07092
Autor:
Wu, Tsung-Han, Biamby, Giscard, Quenum, Jerome, Gupta, Ritwik, Gonzalez, Joseph E., Darrell, Trevor, Chan, David M.
Large Multimodal Models (LMMs) have made significant strides in visual question-answering for single images. Recent advancements like long-context LMMs have allowed them to ingest larger, or even multiple, images. However, the ability to process a la
Externí odkaz:
http://arxiv.org/abs/2407.13766
Autor:
Alcayne, V., Kimura, A., Mendoza, E., Cano-Ott, D., Aberle, O., Álvarez-Velarde, F., Amaducci, S., Andrzejewski, J., Audouin, L., Bécares, V., Babiano-Suarez, V., Bacak, M., Barbagallo, M., Bečvář, F., Bellia, G., Berthoumieux, E., Billowes, J., Bosnar, D., Brown, A., Busso, M., Caamaño, M., Caballero-Ontanaya, L., Calviño, F., Calviani, M., Casanovas, A., Cerutti, F., Chen, Y. H., Chiaveri, E., Colonna, N., Cortés, G., Cortés-Giraldo, M. A., Cosentino, L., Cristallo, S., Damone, L. A., Diakaki, M., Dietz, M., Domingo-Pardo, C., Dressler, R., Dupont, E., Durán, I., Eleme, Z., Fernández-Domınguez, B., Ferrari, A., Finocchiaro, P., Furman, V., Göbel, K., Garg, R., Gawlik-Ramiega, A., Gilardoni, S., Glodariu, T., Gonçalves, I. F., González-Romero, E., Guerrero, C., Gunsing, F., Harada, H., Heinitz, S., Heyse, J., Jenkins, D. G., Jericha, E., Käppeler, F., Kadi, Y., Kivel, N., Kokkoris, M., Kopatch, Y., Krtička, M., Kurtulgil, D., Ladarescu, I., Lederer-Woods, C., Leeb, H., Lerendegui-Marco, J., Meo, S. Lo, Lonsdale, S. J., Macina, D., Manna, A., Martınez, T., Masi, A., Massimi, C., Mastinu, P., Mastromarco, M., Matteucci, F., Maugeri, E. A., Mazzone, A., Mengoni, A., Michalopoulou, V., Milazzo, P. M., Mingrone, F., Musumarra, A., Negret, A., Nolte, R., Ogállar, F., Oprea, A., Patronis, N., Pavlik, A., de Rada, A. Pérez, Perkowski, J., Persanti, L., Porras, I., Praena, J., Quesada, J. M., Radeck, D., Ramos-Doval, D., Rauscher, T., Reifarth, R., Rochman, D., Romanets, Y., Rubbia, C., Sabaté-Gilarte, M., Saxena, A., Schillebeeckx, P., Schumann, D., Smith, A. G., Sosnin, N. V., Stamatopoulos, A., Tagliente, G., Tain, J. L., Talip, T., Tarifeño-Saldivia, A., Tassan-Got, L., Torres-Sánchez, P., Tsinganis, A., Ulrich, J., Urlass, S., Valenta, S., Vannini, G., Variale, V., Vaz, P., Ventura, A., Vlachoudis, V., Vlastou, R., Wallner, A., Woods, P. J., Wright, T., Žugec, P.
The $^{246}$Cm(n,$\gamma$) and $^{248}$Cm(n,$\gamma$) cross-sections have been measured at the Experimental Area 2 (EAR2) of the n_TOF facility at CERN with three C$_6$D$_6$ detectors. This measurement is part of a collective effort to improve the ca
Externí odkaz:
http://arxiv.org/abs/2407.06377