Results 151 to 160 of about 13,981 (216)

Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

arXiv.org
We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. Nemotron 3 Nano was pretrained on 25 trillion text tokens, including more than 3 trillion new unique tokens over Nemotron 2, followed by supervised fine ...
Nvidia Aaron Blakeman, Aaron Grattafiori, Aarti Basant, Abhibha Gupta, Abhinav Khattar, Adi Renduchintala, Aditya Vavre, Akanksha Shukla, A. Bercovich, Aleksander Ficek, Aleksandr Shaposhnikov, Alex Kondratenko, A. Bukharin, Alexandre Milesi, Ali Taghibakhshi, Alisa Liu, Amelia Barton, A. Mahabaleshwarkar, Amir Klein, Amit Zuker, Amnon Geifman, Amy Shen, Anahita Bhiwandiwalla, Andrew Tao, Ann Guan, Anubhav Mandarwal, Arham Mehta, Ashwath Aithal, Ashwin Poojary, A. Ahamed, Asma Kuriparambil Thekkumpate, Ayush Dattagupta, Banghua Zhu, Bardiya Sadeghi, B. Simkin, Ben Lanir, Benedikt Schifferer, Besmira Nushi, Bilal Kartal, B. Rouhani, Boris Ginsburg, Brandon Norick, B. Soubasis, B. Kisačanin, Brian Yu, Bryan Catanzaro, Carlo del Mundo, Chantal Hwang, Charles Wang, Cheng-Ping Hsieh, Chenghao Zhang, Chenhan Yu, Chetan Mungekar, Chintan Patel, Chris Alexiuk, Christopher Parisien, Collin Neale, Damon Mosk-Aoyama, Dan Su, Dane S. Corneil, Daniel Afrimi, Daniel Rohrer, Daniel Serebrenik, Daria Gitman, Daria Levy, Darko Stosic, David Mosallanezhad, Deepak Narayanan, Dhruv Nathawani, Dima Rekesh, Dina Yared, Divyanshu Kakwani, Dong Ahn, Duncan Riach, Dusan Stosic, E. Minasyan, Edward Lin, E. Long, E. Long, Elena Lantz, Ellie Evans, Elliott Ning, Eric Chung, Eric Harper, Eric W. Tramel, Erick Galinkin, Erik Pounds, Evan Briones, E. Bakhturina, Faisal Ladhak, Fay Wang, Fei Jia, Felipe Soares, Feng Chen, Ferenc Galkó, Frankie Siino, Galila Agam, Ganesh Ajjanagadde, Gantavya Bhatt, G. Prasad, George Armstrong, Gerald Shen, G. Batmaz, Grigor Nalbandyan, Haifeng Qian, Harsh Sharma, Hayley Ross, Helen Ngo, Herman Sahota, Hexin Wang, Himanshu Soni, Hiren Upadhyay, Huizi Mao, Huy C Nguyen, Huy Q Nguyen, Iain Cunningham, Ido Shahaf, Igor Gitman, I. Loshchilov, Ivan Moshkov, Izzy Putterman, Jan Kautz, Jane Scowcroft, J. Casper, Jatin Mitra, Jeffrey Glick, Jenny Chen, Jesse Oliver, Jian Zhang, Jiaqi Zeng, Jie Lou, Jimmy Zhang, Jining Huang, Joey Conway, J. Guman, John Kamalu, Johnny Greco, J. Cohen, Joseph Jennings, Joyjit Daw, J. V. Vialard, Junkeun Yi, Jupinder Parmar, Kai Xu, Kan Zhu, Kari Briski, K. Cheung, K. Luna, Keshav Santhanam, Kevin J. Shih, Kezhi Kong, Khushi Bhardwaj, Krishna C. Puvvada, Krzysztof Pawelec, Kumar Anik, Lawrence C. McAfee, Laya Sleiman, Leon Derczynski, Li Ding, Lucas Liebenwein, Luis Vega, Maanu Grover, Maarten Van Segbroeck, Maer Rodrigues de Melo, Makesh Narsimhan Sreedhar, Manoj Kilaru, Maor Ashkenazi, Marc Romeijn, Mark Cai, Markus Kliegl, Maryam Moosaei, Matvei Novikov, Mehrzad Samadi, Melissa Corpuz, Mengru Wang, Meredith Price, Michael Boone, Michael Evans, Miguel Martínez, Mike Chrzanowski, M. Shoeybi, M. Patwary, Nabin Mulepati, Natalie Hereth, Nave Assaf, N. Habibi, Neta Zmora, Netanel Haber, Nicola Sessions, Nidhi Bhatia, Nikhil Jukar, Nikki Pope, Nikolai Ludwig, Nima Tajbakhsh, Nirmal Juluru, Oleksii Hrinchuk, Oleksii Kuchaiev, Olivier Delalleau, O. Olabiyi, Omer Ullman Argov, Ouye Xie, Parth Chadha, Pasha Shamis, Pavlo Molchanov, Pawel M. Morkisz, Peter Dykas, Peter Jin, Pinky Xu, Piotr Januszewski, P. Thombre, Prasoon Varshney, Pritam Gundecha, Qing Miao, Rabeeh Karimi Mahabadi, Ran El-Yaniv, Ran Zilberstein, Rasoul Shafipour, Rich Harang, Rick Izzo, Rima Shahbazyan, Rishabh Garg, Ritika Borkar, Ritu Gala, Riyad Islam, R. Waleffe, Rohit Watve, Roi Koren, Ruoxi Zhang, Russell J. Hewett, R. Prenger, Ryan Timbrook, Sadegh Mahdavi, Sahil Modi, Samuel Kriman, Sanjay Kariyappa, S. Satheesh, Saori Kaji, Satish Pasumarthi, Sean Narentharen, Sean Narenthiran, Seonmyeong Bak, Sergey Kashirsky, Seth Poulos, Shahar Mor, Shanmugam Ramasamy, Shantanu Acharya, Shaona Ghosh, Sharath Turuvekere Sreenivas, S. Thomas, Shiqing Fan, Shreya Gopal, Shrimai Prabhumoye, Shubham Pachori, Shubham Toshniwal, Shuoyang Ding, Siddharth Singh, Simeng Sun, Smita Ithape, Somshubra Majumdar, Soumye Singhal, Stefania Alborghetti, Stephen Ge, Sugam Devare, Sumeet Kumar Barua, Suseella Panguluri, Suyog Gupta, S. Priyadarshi, Syeda Nahida Akter, Tan Bui, Teodor-Dumitru Ene, Terry Kong, Thanh Do, Tijmen Blankevoort, Tom Balough, Tomer Asida, Tomer Bar Natan, T. Konuk, Twinkle Vashishth, Udi Karpas, Ushnish De, Vahid Noorozi, V. Noroozi, V. Srinivasan, V. Elango, V. Korthikanti, V. Kurin, Vitaly Lavrukhin, Wanli Jiang, W. Ahmad, Wei Du, Wei Ping, Wenfei Zhou, Will Jennings, William Zhang, Wojciech Prazuch, Xiaowei Ren, Yashaswi Karnati, Yejin Choi, Yev Meyer, Yi-Fu Wu, Yian Zhang, Ying Lin, Yonatan Geifman, Yonggan Fu, Yoshi Subara, Yoshi Suhara, Yubo Gao, Zach Moshe, Zhen Dong, Zihan Liu, Zijia Chen, Zijie Yan   +311 more
semanticscholar   +1 more source

SCSegamba: Lightweight Structure-Aware Vision Mamba for Crack Segmentation in Structures

Computer Vision and Pattern Recognition
Pixel-level segmentation of structural cracks across various scenarios remains a considerable challenge. Current methods encounter challenges in effectively modeling crack morphology and texture, facing challenges in balancing segmentation quality with ...
Hui Liu, Chen Jia, Fan Shi, Xu Cheng, Shengyong Chen   +4 more
semanticscholar   +1 more source

SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

International Conference on Medical Image Computing and Computer-Assisted Intervention
The Transformer architecture has shown a remarkable ability in modeling global relationships. However, it poses a significant computational challenge when processing high-dimensional medical images. This hinders its development and widespread adoption in
Zhaohu Xing, Tian Ye, Yijun Yang, Guang Liu, Lei Zhu   +4 more
semanticscholar   +1 more source

Jamba: A Hybrid Transformer-Mamba Language Model

arXiv.org
We present Jamba, a new base large language model based on a novel hybrid Transformer-Mamba mixture-of-experts (MoE) architecture. Specifically, Jamba interleaves blocks of Transformer and Mamba layers, enjoying the benefits of both model families.
Opher Lieber, Barak Lenz, Hofit Bata, Gal Cohen, Jhonathan Osin, Itay Dalmedigos, Erez Safahi, S. Meirom, Yonatan Belinkov, S. Shalev-Shwartz, Omri Abend, Raz Alon, Tomer Asida, Amir Bergman, Roman Glozman, Michael Gokhman, Avshalom Manevich, Nir Ratner, N. Rozen, Erez Shwartz, Mor Zusman, Y. Shoham   +21 more
semanticscholar   +1 more source

Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding

International Journal of Computer Vision
State space models (SSMs) have demonstrated remarkable capabilities in natural language processing. Yet, their applicability to video understanding remains underexplored.
Guo Chen, Yifei Huang, Jilan Xu, Baoqi Pei, Zhe Chen, Zhiqi Li, Jiahao Wang, Kunchang Li, Tong Lu, Limin Wang   +9 more
semanticscholar   +1 more source

MambaHSISR: Mamba Hyperspectral Image Super-Resolution

IEEE Transactions on Geoscience and Remote Sensing
One of the main challenges facing hyperspectral image super-resolution is the complex high-dimensional data processing. Mamba leverages its ability to model long-range dependencies of linear complexity to capture the global spatial and spectral ...
Yinghao Xu, Hao Wang, Fei Zhou, Chunbo Luo, Xin Sun, Susanto Rahardja, P. Ren   +6 more
semanticscholar   +1 more source

Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining

International Conference on Medical Image Computing and Computer-Assisted Intervention
Accurate medical image segmentation demands the integration of multi-scale information, spanning from local features to global dependencies. However, it is challenging for existing methods to model long-range global information, where convolutional ...
Jiarun Liu, Hao Yang, Hong-Yu Zhou, Yan Xi, Lequan Yu, Yizhou Yu, Yong Liang, Guangming Shi, Shaoting Zhang, Hairong Zheng, Shanshan Wang   +10 more
semanticscholar   +1 more source

Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation

arXiv.org
In recent advancements in medical image analysis, Convolutional Neural Networks (CNN) and Vision Transformers (ViT) have set significant benchmarks.
Ziyang Wang, Jian-Qing Zheng, Yichi Zhang, Ge Cui, Lei Li   +4 more
semanticscholar   +1 more source

EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba

AAAI Conference on Artificial Intelligence
Prior efforts in light-weight model development mainly centered on CNN and Transformer-based designs yet faced persistent challenges. CNNs adept at local feature extraction compromise resolution while Transformers offer global reach but escalate ...
Xiaohuan Pei, Tao Huang, Chang Xu
semanticscholar   +1 more source

MedMamba: Vision Mamba for Medical Image Classification

arXiv.org
Since the era of deep learning, convolutional neural networks (CNNs) and vision transformers (ViTs) have been extensively studied and widely used in medical image classification tasks.
Yubiao Yue, Zhenzhang Li
semanticscholar   +1 more source