Zobrazeno 1 - 10
of 6 385
pro vyhledávání: '"A. Ganti"'
We present a toolkit for creating low-cost Mixture-of-Domain-Experts (MOE) from trained models. The toolkit can be used for creating a mixture from models or from adapters. We perform extensive tests and offer guidance on defining the architecture of
Externí odkaz:
http://arxiv.org/abs/2408.17280
Autor:
Adebola, Simeon, Sadjadpour, Tara, El-Refai, Karim, Panitch, Will, Ma, Zehan, Lin, Roy, Qiu, Tianshuang, Ganti, Shreya, Le, Charlotte, Drake, Jaimyn, Goldberg, Ken
In Gasket Assembly, a deformable gasket must be aligned and pressed into a narrow channel. This task is common for sealing surfaces in the manufacturing of automobiles, appliances, electronics, and other products. Gasket Assembly is a long-horizon, h
Externí odkaz:
http://arxiv.org/abs/2408.12593
Padding is often used in tuning LLM models by adding special tokens to shorter training examples to match the length of the longest sequence in each batch. While this ensures uniformity for batch processing, it introduces inefficiencies by including
Externí odkaz:
http://arxiv.org/abs/2407.09105
This research looks at using AI/ML to achieve centimeter-level user positioning in 6G applications such as the Industrial Internet of Things (IIoT). Initial results show that our AI/ML-based method can estimate user positions with an accuracy of 17 c
Externí odkaz:
http://arxiv.org/abs/2406.14458
The objective of this work is to assess the impact of parameter uncertainty on hypersonic aerothermal surface heating predictions in Reynolds-Averaged Navier-Stokes (RANS) simulations using non-intrusive uncertainty quantification (UQ) techniques. RA
Externí odkaz:
http://arxiv.org/abs/2405.15875
Autor:
Wertheimer, Davis, Rosenkranz, Joshua, Parnell, Thomas, Suneja, Sahil, Ranganathan, Pavithra, Ganti, Raghu, Srivatsa, Mudhakar
This technical report describes the design and training of novel speculative decoding draft models, for accelerating the inference speeds of large language models in a production environment. By conditioning draft predictions on both context vectors
Externí odkaz:
http://arxiv.org/abs/2404.19124
Ensuring adequate wireless coverage in upcoming communication technologies such as 6G is expected to be challenging. This is because user demands of higher datarate require an increase in carrier frequencies, which in turn reduce the diffraction effe
Externí odkaz:
http://arxiv.org/abs/2404.09215
Autor:
Hari, Kush, Kim, Hansoul, Panitch, Will, Srinivas, Kishore, Schorp, Vincent, Dharmarajan, Karthik, Ganti, Shreya, Sadjadpour, Tara, Goldberg, Ken
We present STITCH: an augmented dexterity pipeline that performs Suture Throws Including Thread Coordination and Handoffs. STITCH iteratively performs needle insertion, thread sweeping, needle extraction, suture cinching, needle handover, and needle
Externí odkaz:
http://arxiv.org/abs/2404.05151
Accurate decoding of Uplink Control Information (UCI) on the Physical Uplink Control Channel (PUCCH) is essential for enabling 5G wireless links. This paper explores an AI/ML-based receiver design for PUCCH Format 0. Format 0 signaling encodes the UC
Externí odkaz:
http://arxiv.org/abs/2404.15243
Autor:
Wang, Tianshi, Li, Jinyang, Wang, Ruijie, Kara, Denizhan, Liu, Shengzhong, Wertheimer, Davis, Viros-i-Martin, Antoni, Ganti, Raghu, Srivatsa, Mudhakar, Abdelzaher, Tarek
This paper introduces SudokuSens, a generative framework for automated generation of training data in machine-learning-based Internet-of-Things (IoT) applications, such that the generated synthetic data mimic experimental configurations not encounter
Externí odkaz:
http://arxiv.org/abs/2402.02275