Zobrazeno 1 - 10
of 6 226
pro vyhledávání: '"Muralidharan, P."'
The spin-valley or Kramers qubit promises significantly enhanced spin-valley lifetimes due to strong coupling of the electrons' spin to their momentum (valley) degrees of freedom. In transition metal dichalcogenides (TMDCs) such spin-valley locking i
Externí odkaz:
http://arxiv.org/abs/2410.21814
Autor:
Liu, Shih-Yang, Yang, Huck, Wang, Chein-Yi, Fung, Nai Chit, Yin, Hongxu, Sakr, Charbel, Muralidharan, Saurav, Cheng, Kwang-Ting, Kautz, Jan, Wang, Yu-Chiang Frank, Molchanov, Pavlo, Chen, Min-Hung
In this work, we re-formulate the model compression problem into the customized compensation problem: Given a compressed model, we aim to introduce residual low-rank paths to compensate for compression errors under customized requirements from users
Externí odkaz:
http://arxiv.org/abs/2410.21271
Autor:
Fang, Gongfan, Yin, Hongxu, Muralidharan, Saurav, Heinrich, Greg, Pool, Jeff, Kautz, Jan, Molchanov, Pavlo, Wang, Xinchao
Large Language Models (LLMs) are distinguished by their massive parameter counts, which typically result in significant redundancy. This work introduces MaskLLM, a learnable pruning method that establishes Semi-structured (or ``N:M'') Sparsity in LLM
Externí odkaz:
http://arxiv.org/abs/2409.17481
Autor:
Muralidharan, Varun, Cline, James M.
It has been proposed that the accelerated expansion of the universe can be explained by the merging of our universe with baby universes, resulting in dark energy with a phantom-like equation of state. However, the evidence in favor of it did not incl
Externí odkaz:
http://arxiv.org/abs/2408.13306
Autor:
Sreenivas, Sharath Turuvekere, Muralidharan, Saurav, Joshi, Raviraj, Chochowski, Marcin, Patwary, Mostofa, Shoeybi, Mohammad, Catanzaro, Bryan, Kautz, Jan, Molchanov, Pavlo
We present a comprehensive report on compressing the Llama 3.1 8B and Mistral NeMo 12B models to 4B and 8B parameters, respectively, using pruning and distillation. We explore two distinct pruning strategies: (1) depth pruning and (2) joint hidden/at
Externí odkaz:
http://arxiv.org/abs/2408.11796
This project investigates the efficacy of Large Language Models (LLMs) in understanding and extracting scientific knowledge across specific domains and to create a deep learning framework: Knowledge AI. As a part of this framework, we employ pre-trai
Externí odkaz:
http://arxiv.org/abs/2408.04651
Autor:
Muralidharan, Saurav, Sreenivas, Sharath Turuvekere, Joshi, Raviraj, Chochowski, Marcin, Patwary, Mostofa, Shoeybi, Mohammad, Catanzaro, Bryan, Kautz, Jan, Molchanov, Pavlo
Large language models (LLMs) targeting different deployment scales and sizes are currently produced by training each variant from scratch; this is extremely compute-intensive. In this paper, we investigate if pruning an existing LLM and then re-train
Externí odkaz:
http://arxiv.org/abs/2407.14679
Spintronic-based neuromorphic hardware offers high-density and rapid data processing at nanoscale lengths by leveraging magnetic configurations like skyrmion and domain walls. Here, we present the maximal hardware implementation of a convolutional ne
Externí odkaz:
http://arxiv.org/abs/2407.08469
Autor:
Low, Yen Sia, Jackson, Michael L., Hyde, Rebecca J., Brown, Robert E., Sanghavi, Neil M., Baldwin, Julian D., Pike, C. William, Muralidharan, Jananee, Hui, Gavin, Alexander, Natasha, Hassan, Hadeel, Nene, Rahul V., Pike, Morgan, Pokrzywa, Courtney J., Vedak, Shivam, Yan, Adam Paul, Yao, Dong-han, Zipursky, Amy R., Dinh, Christina, Ballentine, Philip, Derieg, Dan C., Polony, Vladimir, Chawdry, Rehan N., Davies, Jordan, Hyde, Brigham B., Shah, Nigam H., Gombar, Saurabh
Evidence to guide healthcare decisions is often limited by a lack of relevant and trustworthy literature as well as difficulty in contextualizing existing research for a specific patient. Large language models (LLMs) could potentially address both ch
Externí odkaz:
http://arxiv.org/abs/2407.00541
Autor:
Weber, Bent, Fuhrer, Michael S, Sheng, Xian-Lei, Yang, Shengyuan A, Thomale, Ronny, Shamim, Saquib, Molenkamp, Laurens W, Cobden, David, Pesin, Dmytro, Zandvliet, Harold J W, Bampoulis, Pantelis, Claessen, Ralph, Menges, Fabian R, Gooth, Johannes, Felser, Claudia, Shekhar, Chandra, Tadich, Anton, Zhao, Mengting, Edmonds, Mark T, Jia, Junxiang, Bieniek, Maciej, Väyrynen, Jukka I, Culcer, Dimitrie, Muralidharan, Bhaskaran, Nadeem, Muhammad
2D topological insulators promise novel approaches towards electronic, spintronic, and quantum device applications. This is owing to unique features of their electronic band structure, in which bulk-boundary correspondences enforces the existence of
Externí odkaz:
http://arxiv.org/abs/2406.14209