Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Mahajan, Kshiteej"'
Autor:
Singh, Avi, Co-Reyes, John D., Agarwal, Rishabh, Anand, Ankesh, Patil, Piyush, Garcia, Xavier, Liu, Peter J., Harrison, James, Lee, Jaehoon, Xu, Kelvin, Parisi, Aaron, Kumar, Abhishek, Alemi, Alex, Rizkowsky, Alex, Nova, Azade, Adlam, Ben, Bohnet, Bernd, Elsayed, Gamaleldin, Sedghi, Hanie, Mordatch, Igor, Simpson, Isabelle, Gur, Izzeddin, Snoek, Jasper, Pennington, Jeffrey, Hron, Jiri, Kenealy, Kathleen, Swersky, Kevin, Mahajan, Kshiteej, Culp, Laura, Xiao, Lechao, Bileschi, Maxwell L., Constant, Noah, Novak, Roman, Liu, Rosanne, Warkentin, Tris, Qian, Yundi, Bansal, Yamini, Dyer, Ethan, Neyshabur, Behnam, Sohl-Dickstein, Jascha, Fiedel, Noah
Fine-tuning language models~(LMs) on human-generated data remains a prevalent practice. However, the performance of such models is often limited by the quantity and diversity of high-quality human data. In this paper, we explore whether we can go bey
Externí odkaz:
http://arxiv.org/abs/2312.06585
Autor:
Freeman, C. Daniel, Culp, Laura, Parisi, Aaron, Bileschi, Maxwell L, Elsayed, Gamaleldin F, Rizkowsky, Alex, Simpson, Isabelle, Alemi, Alex, Nova, Azade, Adlam, Ben, Bohnet, Bernd, Mishra, Gaurav, Sedghi, Hanie, Mordatch, Igor, Gur, Izzeddin, Lee, Jaehoon, Co-Reyes, JD, Pennington, Jeffrey, Xu, Kelvin, Swersky, Kevin, Mahajan, Kshiteej, Xiao, Lechao, Liu, Rosanne, Kornblith, Simon, Constant, Noah, Liu, Peter J., Novak, Roman, Qian, Yundi, Fiedel, Noah, Sohl-Dickstein, Jascha
We introduce and study the problem of adversarial arithmetic, which provides a simple yet challenging testbed for language model alignment. This problem is comprised of arithmetic questions posed in natural language, with an arbitrary adversarial str
Externí odkaz:
http://arxiv.org/abs/2311.07587
Autor:
Mahajan, Kshiteej, Balasubramanian, Arjun, Singhvi, Arjun, Venkataraman, Shivaram, Akella, Aditya, Phanishayee, Amar, Chawla, Shuchi
Modern distributed machine learning (ML) training workloads benefit significantly from leveraging GPUs. However, significant contention ensues when multiple such workloads are run atop a shared cluster of GPUs. A key question is how to fairly apporti
Externí odkaz:
http://arxiv.org/abs/1907.01484
Publikováno v:
IndraStra Global.
Modern data processing clusters are highly dynamic – both in terms of the number of concurrently running jobs and their resource usage. To improve job performance, recent works have focused on optimizing the cluster scheduler and the jobs’ query
Publikováno v:
2014 Sixth International Conference on Communication Systems & Networks (COMSNETS); 2014, p1-8, 8p
Publikováno v:
2011 IEEE 5th International Conference on Internet Multimedia Systems Architecture & Application; 1/ 1/2011, p1-6, 6p