Zobrazeno 1 - 10
of 5 440
pro vyhledávání: '"P. Nussbaum"'
Autor:
Shalev-Shwartz, Shai, Shashua, Amnon, Beniamini, Gal, Levine, Yoav, Sharir, Or, Wies, Noam, Ben-Shaul, Ido, Nussbaum, Tomer, Peled, Shir Granot
Artificial Expert Intelligence (AEI) seeks to transcend the limitations of both Artificial General Intelligence (AGI) and narrow AI by integrating domain-specific expertise with critical, precise reasoning capabilities akin to those of top human expe
Externí odkaz:
http://arxiv.org/abs/2412.02441
Autor:
Suresh, Tarun, Reddy, Revanth Gangi, Xu, Yifei, Nussbaum, Zach, Mulyar, Andriy, Duderstadt, Brandon, Ji, Heng
Effective code retrieval plays a crucial role in advancing code generation, bug fixing, and software maintenance, particularly as software systems increase in complexity. While current code embedding models have demonstrated promise in retrieving cod
Externí odkaz:
http://arxiv.org/abs/2412.01007
Autor:
Kapoor, K., Hoseini, S., Choi, J., Nussbaum, B. E., Zhang, Y., Shetty, K., Skaar, C., Ward, M., Wilson, L., Shinbrough, K., Edwards, E., Wiltfong, R., Lualdi, C. P., Cohen, Offir, Kwiat, P. G., Lorenz, V. O.
We present a quantum network that distributes entangled photons between the University of Illinois Urbana-Champaign and a public library in Urbana. The network allows members of the public to perform measurements on the photons. We describe its desig
Externí odkaz:
http://arxiv.org/abs/2410.06398
This technical report describes the training of nomic-embed-vision, a highly performant, open-code, open-weights image embedding model that shares the same latent space as nomic-embed-text. Together, nomic-embed-vision and nomic-embed-text form the f
Externí odkaz:
http://arxiv.org/abs/2406.18587
Autor:
Jalota, Rricha, Verwimp, Lyan, Nussbaum-Thom, Markus, Mousa, Amr, Argueta, Arturo, Oualil, Youssef
Neural Network Language Models (NNLMs) for Virtual Assistants (VAs) are generally language-, region-, and in some cases, device-dependent, which increases the effort to scale and maintain them. Combining NNLMs for one or more of the categories is one
Externí odkaz:
http://arxiv.org/abs/2403.18783
This technical report describes the training of nomic-embed-text-v1, the first fully reproducible, open-source, open-weights, open-data, 8192 context length English text embedding model that outperforms both OpenAI Ada-002 and OpenAI text-embedding-3
Externí odkaz:
http://arxiv.org/abs/2402.01613
Autor:
Anand, Yuvanesh, Nussbaum, Zach, Treat, Adam, Miller, Aaron, Guo, Richard, Schmidt, Ben, Community, GPT4All, Duderstadt, Brandon, Mulyar, Andriy
Large language models (LLMs) have recently achieved human-level performance on a range of professional and academic benchmarks. The accessibility of these models has lagged behind their performance. State-of-the-art LLMs require costly infrastructure
Externí odkaz:
http://arxiv.org/abs/2311.04931
Autor:
Emili, Leonardo, Fraga-Silva, Thiago, Pusateri, Ernest, Nußbaum-Thom, Markus, Oualil, Youssef
We study model pruning methods applied to Transformer-based neural network language models for automatic speech recognition. We explore three aspects of the pruning frame work, namely criterion, method and scheduler, analyzing their contribution in t
Externí odkaz:
http://arxiv.org/abs/2310.03424
Publikováno v:
Solid Earth, Vol 15, Pp 1445-1463 (2024)
This study employs numerical simulations based on the limit analysis (LA) method to calculate the stress distribution in a model that includes a basal detachment, featuring the lateral termination of a generic fault under compression. We conduct 2500
Externí odkaz:
https://doaj.org/article/0c53861b1d45437c8c90989cada81108
Publikováno v:
Journal of Dairy Science, Vol 107, Iss 12, Pp 10724-10737 (2024)
ABSTRACT: As the call for an international standard for milk from grassland-based production systems continues to grow, so too do the monitoring and evaluation policies surrounding this topic. Individual stipulations by countries and milk producers t
Externí odkaz:
https://doaj.org/article/02a05f39cf7641d6acc70f9e56b97fae