Shrinking the Giant : Quasi-Weightless Transformers for Low Energy Inference

Autor: Nag, Shashank, Bacellar, Alan T. L., Susskind, Zachary, Jha, Anshul, Liberty, Logan, Sivakumar, Aishwarya, John, Eugene B., Kailas, Krishnan, Lima, Priscila M. V., Yadwadkar, Neeraja J., Franca, Felipe M. G., John, Lizy K.

Transformers are set to become ubiquitous with applications ranging from chatbots and educational assistants to visual recognition and remote sensing. However, their increasing computational and memory demands is resulting in growing energy consumpti

Externí odkaz: http://arxiv.org/abs/2411.01818

emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography

Autor: Sivakumar, Viswanath, Seely, Jeffrey, Du, Alan, Bittner, Sean R, Berenzweig, Adam, Bolarinwa, Anuoluwapo, Gramfort, Alexandre, Mandel, Michael I

Surface electromyography (sEMG) non-invasively measures signals generated by muscle activity with sufficient sensitivity to detect individual spinal neurons and richness to identify dozens of gestures and their nuances. Wearable wrist-based sEMG sens

Externí odkaz: http://arxiv.org/abs/2410.20081

Transfer Reinforcement Learning in Heterogeneous Action Spaces using Subgoal Mapping

Autor: Sivakumar, Kavinayan P., Zhang, Yan, Bell, Zachary, Nivison, Scott, Zavlanos, Michael M.

In this paper, we consider a transfer reinforcement learning problem involving agents with different action spaces. Specifically, for any new unseen task, the goal is to use a successful demonstration of this task by an expert agent in its action spa

Externí odkaz: http://arxiv.org/abs/2410.14484

Movie Gen: A Cast of Media Foundation Models

Autor: Polyak, Adam, Zohar, Amit, Brown, Andrew, Tjandra, Andros, Sinha, Animesh, Lee, Ann, Vyas, Apoorv, Shi, Bowen, Ma, Chih-Yao, Chuang, Ching-Yao, Yan, David, Choudhary, Dhruv, Wang, Dingkang, Sethi, Geet, Pang, Guan, Ma, Haoyu, Misra, Ishan, Hou, Ji, Wang, Jialiang, Jagadeesh, Kiran, Li, Kunpeng, Zhang, Luxin, Singh, Mannat, Williamson, Mary, Le, Matt, Yu, Matthew, Singh, Mitesh Kumar, Zhang, Peizhao, Vajda, Peter, Duval, Quentin, Girdhar, Rohit, Sumbaly, Roshan, Rambhatla, Sai Saketh, Tsai, Sam, Azadi, Samaneh, Datta, Samyak, Chen, Sanyuan, Bell, Sean, Ramaswamy, Sharadh, Sheynin, Shelly, Bhattacharya, Siddharth, Motwani, Simran, Xu, Tao, Li, Tianhe, Hou, Tingbo, Hsu, Wei-Ning, Yin, Xi, Dai, Xiaoliang, Taigman, Yaniv, Luo, Yaqiao, Liu, Yen-Cheng, Wu, Yi-Chiao, Zhao, Yue, Kirstain, Yuval, He, Zecheng, He, Zijian, Pumarola, Albert, Thabet, Ali, Sanakoyeu, Artsiom, Mallya, Arun, Guo, Baishan, Araya, Boris, Kerr, Breena, Wood, Carleigh, Liu, Ce, Peng, Cen, Vengertsev, Dimitry, Schonfeld, Edgar, Blanchard, Elliot, Juefei-Xu, Felix, Nord, Fraylie, Liang, Jeff, Hoffman, John, Kohler, Jonas, Fire, Kaolin, Sivakumar, Karthik, Chen, Lawrence, Yu, Licheng, Gao, Luya, Georgopoulos, Markos, Moritz, Rashel, Sampson, Sara K., Li, Shikai, Parmeggiani, Simone, Fine, Steve, Fowler, Tara, Petrovic, Vladan, Du, Yuming

We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of

Externí odkaz: http://arxiv.org/abs/2410.13720

Llettuce: An Open Source Natural Language Processing Tool for the Translation of Medical Terms into Uniform Clinical Encoding

Autor: Mitchell-White, James, Omdivar, Reza, Urwin, Esmond, Sivakumar, Karthikeyan, Li, Ruizhe, Rae, Andy, Wang, Xiaoyan, Mina, Theresia, Chambers, John, Figueredo, Grazziela, Quinlan, Philip R

This paper introduces Llettuce, an open-source tool designed to address the complexities of converting medical terms into OMOP standard concepts. Unlike existing solutions such as the Athena database search and Usagi, which struggle with semantic nua

Externí odkaz: http://arxiv.org/abs/2410.09076