Zobrazeno 1 - 10
of 36 157
pro vyhledávání: '"Harris, A G"'
Autor:
Giliberti, Jeff, Harris, David G.
One main genre of algorithmic derandomization comes from the construction of probability distributions with small support that fool a randomized algorithm. This is especially well-suited to parallelization, i.e. NC algorithms. A significant abstracti
Externí odkaz:
http://arxiv.org/abs/2411.18028
Autor:
Diamandi, Hilel Hagai, Luo, Yizhi, Mason, David, Kanmaz, Tevfik Bulent, Ghosh, Sayan, Pavlovich, Margaret, Yoon, Taekwan, Behunin, Ryan, Puri, Shruti, Harris, Jack G. E., Rakich, Peter T.
High-fidelity quantum optomechanical control of a mechanical oscillator requires the ability to perform efficient, low-noise operations on long-lived phononic excitations. Microfabricated high-overtone bulk acoustic wave resonators ($\mathrm{\mu}$HBA
Externí odkaz:
http://arxiv.org/abs/2410.18037
This study introduces an approach to optimize Parameter Efficient Fine Tuning (PEFT) for Pretrained Language Models (PLMs) by implementing a Shared Low Rank Adaptation (ShareLoRA). By strategically deploying ShareLoRA across different layers and adap
Externí odkaz:
http://arxiv.org/abs/2406.10785
Deploying Large Language Models (LLMs) locally on mobile devices presents a significant challenge due to their extensive memory requirements. In this paper, we introduce LinguaLinked, a system for decentralized, distributed LLM inference on mobile de
Externí odkaz:
http://arxiv.org/abs/2312.00388
Autor:
Chou, Aaron, Irwin, Kent, Maruyama, Reina H., Baker, Oliver K., Bartram, Chelsea, Berggren, Karl K., Cancelo, Gustavo, Carney, Daniel, Chang, Clarence L., Cho, Hsiao-Mei, Garcia-Sciveres, Maurice, Graham, Peter W., Habib, Salman, Harnik, Roni, Harris, J. G. E., Hertel, Scott A., Hume, David B., Khatiwada, Rakshya, Kovachy, Timothy L., Kurinsky, Noah, Lamoreaux, Steve K., Lehnert, Konrad W., Leibrandt, David R., Li, Dale, Loer, Ben, Martínez-Rincón, Julián, McCuller, Lee, Moore, David C., Mueller, Holger, Pena, Cristian, Pooser, Raphael C., Pyle, Matt, Rajendran, Surjeet, Safronova, Marianna S., Schuster, David I., Shaw, Matthew D., Spiropulu, Maria, Stankus, Paul, Sushkov, Alexander O., Winslow, Lindley, Xie, Si, Zurek, Kathryn M.
Strong motivation for investing in quantum sensing arises from the need to investigate phenomena that are very weakly coupled to the matter and fields well described by the Standard Model. These can be related to the problems of dark matter, dark sec
Externí odkaz:
http://arxiv.org/abs/2311.01930
Large Language Models' safety remains a critical concern due to their vulnerability to adversarial attacks, which can prompt these systems to produce harmful responses. In the heart of these systems lies a safety classifier, a computational model tra
Externí odkaz:
http://arxiv.org/abs/2311.00172
Autor:
Harris, Robert G.1
Publikováno v:
Vital Speeches of the Day. 4/1/89, Vol. 55 Issue 12, p377-381. 5p.
Publikováno v:
Journal of International Accounting Research. Oct2024, Vol. 23 Issue 3, p29-49. 21p.
Autor:
Ayres, N. J., Ban, G., Bison, G., Bodek, K., Bondar, V., Bouillaud, T., Bowles, D., Chanel, E., Chen, W., Chiu, P. -J., Crawford, C. B., Naviliat-Cuncic, O., Doorenbos, C. B., Emmenegger, S., Fertl, M., Fratangelo, A., Griffith, W. C., Grujic, Z. D., Harris, P. G., Kirch, K., Kletzl, V., Krempel, J., Lauss, B., Lefort, T., Lejuez, A., Li, R., Mullan, P., Pacura, S., Pais, D., Piegsa, F. M., Rienäcker, I., Ries, D., Pignol, G., Rebreyend, D., Roccia, S., Rozpedzik, D., Saenz-Arevalo, W., Schmidt-Wellenburg, P., Schnabel, A., Segarra, E. P., Severijns, N., Svirina, K., Dinani, R. Tavakoli, Thorne, J., Vankeirsbilck, J., Voigt, J., Yazdandoost, N., Zejma, J., Ziehl, N., Zsigmond, G.
High-precision searches for an electric dipole moment of the neutron (nEDM) require stable and uniform magnetic field environments. We present the recent achievements of degaussing and equilibrating the magnetically shielded room (MSR) for the n2EDM
Externí odkaz:
http://arxiv.org/abs/2309.16877
Jailbreak vulnerabilities in Large Language Models (LLMs), which exploit meticulously crafted prompts to elicit content that violates service guidelines, have captured the attention of research communities. While model owners can defend against indiv
Externí odkaz:
http://arxiv.org/abs/2309.05274