6 citations · 16 across the 10 of their papers we have counts for
10 papers
NEBULA: Do We Evaluate Vision-Language-Action Agents Correctly?
Jierui Peng, Yanyan Zhang, Yicheng Duan +3
The evaluation of Vision-Language-Action (VLA) agents is hindered by the coarse, end-task success metric that fails to provide precise skill diagnosis or measure robustness to real…
Quantum Algorithm for Protein Structure Prediction Using the Face-Centered Cubic Lattice
Rui-Hao Li, Hakan Doga, Bryan Raubenolt +16
In this work, we present the first implementation of the face-centered cubic (FCC) lattice model for protein structure prediction with a quantum algorithm. Our motivation to encode…
Irrelevant Pixels are Everywhere: Find and Exclude Them for More Efficient Computer Vision
Caleb Tung, Abhinav Goel, Xiao Hu +5
Computer vision is often performed using Convolutional Neural Networks (CNNs). CNNs are compute-intensive and challenging to deploy on power-contrained systems such as mobile and I…
Give me a knee radiograph, I will tell you where the knee joint area is: a deep convolutional neural network adventure
Shi Yan, Taghi Ramazanian, Elham Sagheb +5
Knee pain is undoubtedly the most common musculoskeletal symptom that impairs quality of life, confines mobility and functionality across all ages. Knee pain is clinically evaluate…
Absolute Value Constraint: The Reason for Invalid Performance Evaluation Results of Neural Network Models for Stock Price Prediction
Yi Wei
Neural networks for stock price prediction(NNSPP) have been popular for decades. However, most of its study results remain in the research paper and cannot truly play a role in the…
MARS: Malleable Actor-Critic Reinforcement Learning Scheduler
Betis Baheri, Jacob Tronge, Bo Fang +3
In this paper, we introduce MARS, a new scheduling system for HPC-cloud infrastructures based on a cost-aware, flexible reinforcement learning approach, which serves as an intermed…
Quantified Spectrum Sharing: Motivation, Approach, and Benefits
Nilesh Khambekar, Chad Spooner, Vipin Chaudhary
A significant portion of the radio frequency spectrum remains underutilized with exclusive and static allocation of spectrum. The growing demand for spectrum has spurred a need for…
MUSE: A Methodology for Characterizing and Quantifying the Use of Spectrum
Nilesh Khambekar, Chad M. Spooner, Vipin Chaudhary
Dynamic spectrum sharing paradigm is envisaged to meet the growing demand for the Radio Frequency (RF) spectrum. There exist several technical, regulatory, and business impediments…
Maximizing Spectrum Availability and Exploitation: How to Maximize Spectrum Sharing Benefits to the Incumbents?
Nilesh Khambekar, Chad M. Spooner, Vipin Chaudhary
A significant portion of the radio frequency spectrum remains underutilized due to exclusive and static allocation of spectrum. Provisioning secondary access to the underutilized s…
Going Towards Discretized Spectrum Space: Quantification of Spectrum Consumption Spaces and a Quantified Spectrum Access Paradigm
Nilesh khambekar, Chad M. Spooner, Vipin Chaudhary
Dynamic spectrum sharing approach is a paradigm shift from the conventional static and exclusive approach to spectrum allocation. The existing methodologies to define use of the sp…