Zobrazeno 1 - 10
of 23 446
pro vyhledávání: '"Narang, A."'
Autor:
Zhong, Ming, Zhang, Aston, Wang, Xuewei, Hou, Rui, Xiong, Wenhan, Zhu, Chenguang, Chen, Zhengxing, Tan, Liang, Bi, Chloe, Lewis, Mike, Popuri, Sravya, Narang, Sharan, Kambadur, Melanie, Mahajan, Dhruv, Edunov, Sergey, Han, Jiawei, van der Maaten, Laurens
The development and evaluation of Large Language Models (LLMs) have largely focused on individual capabilities. However, this overlooks the intersection of multiple abilities across different types of expertise that are often required for real-world
Externí odkaz:
http://arxiv.org/abs/2409.19951
Autor:
Narang, Mayank, Puravankara, Manoj, Vedantham, H. K., Chandra, C. H. Ishwara, De, Ayanabha, Tyagi, Himanshu, Banerjee, Bihan, Nayak, Prasanta K., Surya, Arun, Shridharan, B., Pathak, Vinod C., Tripathi, Mihir
Coherent radio emission with properties similar to planetary auroral signals has been reported from GJ 1151, a quiescent, slow-rotating mid-M star, by the LOFAR Two-metre (120-170 MHz) Sky Survey (LoTSS). The observed {LOFAR} emission is fairly brigh
Externí odkaz:
http://arxiv.org/abs/2409.18507
Autor:
De, Ayanabha, Narang, Mayank, Puravankara, Manoj, Baskaran, Shridharan, Tyagi, Himanshu, Banerjee, Bihan, Nayak, Prasanta Kumar, Surya, Arun
In this work, we have carried out a systematic analysis of the VLASS quick look catalogs together with \textit{Gaia DR3} to identify the optical counterparts of 3~GHz radio emitters within 500~pc to obtain a homogeneous statistical sample of stellar
Externí odkaz:
http://arxiv.org/abs/2409.18466
Autor:
Udvarhelyi, Péter, Narang, Prineha
Defect emitters in silicon are promising contenders as building blocks of solid-state quantum repeaters and sensor networks. Here we investigate a family of possible isoelectronic emitter defect complexes from a design standpoint. We show that the id
Externí odkaz:
http://arxiv.org/abs/2409.10746
Autor:
Arya, Anuraag, Bilkhu, Harmanjeet Singh, Vishwakarma, Sandeep, Belatikar, Hrishikesh, Bhalerao, Varun, Ghodgaonkar, Abhijeet, Koyande, Jayprakash G., Marathe, Aditi, Mithun, N. P. S., Narang, Sanjoli, Nimbalkar, Sudhanshu, Page, Pranav, Palit, Sourav, Patel, Arpit, Shetye, Amit, Tallur, Siddharth, Tendulkar, Shriharsh, Vadawale, Santosh, Waratkar, Gaurav
Hard X-ray photons with energies in the range of hundreds of keV typically undergo Compton scattering when they are incident on a detector. In this process, an incident photon deposits a fraction of its energy at the point of incidence and continues
Externí odkaz:
http://arxiv.org/abs/2409.08822
Autor:
Huber, Patrick, Einolghozati, Arash, Conway, Rylan, Narang, Kanika, Smith, Matt, Nayyar, Waqar, Sagar, Adithya, Aly, Ahmed, Shrivastava, Akshat
Distilling conversational skills into Small Language Models (SLMs) with approximately 1 billion parameters presents significant challenges. Firstly, SLMs have limited capacity in their model parameters to learn extensive knowledge compared to larger
Externí odkaz:
http://arxiv.org/abs/2408.11219
In this work we introduce the DODAG-X protocol for multipartite entanglement distribution in quantum networks. Leveraging the power of Destination Oriented Directed Acyclic Graphs (DODAGs), our protocol optimizes resource consumption and enhances rob
Externí odkaz:
http://arxiv.org/abs/2408.07118
For both humans and robots, the sense of touch, known as tactile sensing, is critical for performing contact-rich manipulation tasks. Three key challenges in robotic tactile sensing are 1) interpreting sensor signals, 2) generating sensor signals in
Externí odkaz:
http://arxiv.org/abs/2408.06506
Autor:
Noseworthy, Michael, Tang, Bingjie, Wen, Bowen, Handa, Ankur, Roy, Nicholas, Fox, Dieter, Ramos, Fabio, Narang, Yashraj, Akinola, Iretiayo
We present FORGE, a method that enables sim-to-real transfer of contact-rich manipulation policies in the presence of significant pose uncertainty. FORGE combines a force threshold mechanism with a dynamics randomization scheme during policy learning
Externí odkaz:
http://arxiv.org/abs/2408.04587
Over the past decade, there has been tremendous progress in the domain of synthetic media generation. This is mainly due to the powerful methods based on generative adversarial networks (GANs). Very recently, diffusion probabilistic models, which are
Externí odkaz:
http://arxiv.org/abs/2408.02078