System Performance

System performance research focuses on optimizing the efficiency and accuracy of various computational systems, from machine learning models to robotic controllers and even quantum computers. Current research emphasizes improving model architectures (e.g., graph-oriented databases for language models, retention-based networks for multi-agent reinforcement learning) and training techniques (e.g., hard sample mining, co-optimization of design and control), while also addressing issues like fairness, robustness, and explainability. These advancements have significant implications for diverse fields, impacting the development of more efficient and reliable AI systems, improved medical diagnostics, and enhanced manufacturing processes.

Papers

December 10, 2023

The performance of multiple language models in identifying offensive language on social media
Hao Li, Brandon Bennett
Language Model Natural Language Processing Social Medium System Performance Text Classification Information Retrieval Offensive Language Content Filtering

December 8, 2023

On the Performance of Temporal Difference Learning With Neural Networks
Haoxing Tian, Ioannis Ch. Paschalidis, Alex Olshevsky
Neural Network System Performance Function Approximation Temporal Difference Learning Temporal Difference Temporal Difference Algorithm

December 2, 2023

Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis
Kiran Thorat, Jiahui Zhao, Yaotian Liu, Hongwu Peng, Xi Xie, Bin Lei, Jeff Zhang, Caiwen Ding
System Performance Program Synthesis Iterative Refinement Hardware Design Advanced Large Language Model Code Synthesis

November 29, 2023

Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
Xiaoge Zhang, Xiao-Lin Wang, Fenglei Fan, Yiu-Ming Cheung, Indranil Bose
Neural Network System Performance Causal Discovery Domain Knowledge Directed Acyclic Graph Causal Objective Function Causal Hierarchy Causality Based Learning

November 28, 2023

Empowering COVID-19 Detection: Optimizing Performance Through Fine-Tuned EfficientNet Deep Learning Architecture
Md. Alamin Talukder, Md. Abu Layek, Mohsin Kazi, Md Ashraf Uddin, Sunil Aryal
System Performance COVID 19 Detection Efficient Deep COVID 19 Diagnosis Chest X Ray Datasets Lung Texture COVID 19 Chest X Ray

November 22, 2023

Improving performance of heart rate time series classification by grouping subjects
Michael Beekhuizen, Arman Naseri, David Tax, Ivo van der Bilt, Marcel Reinders
System Performance Multi Subject Activity Classification Inter Subject

November 17, 2023

November 16, 2023

November 14, 2023

November 12, 2023

Analytical Verification of Performance of Deep Neural Network Based Time-Synchronized Distribution System State Estimation
Behrouz Azimian, Shiva Moshtagh, Anamitra Pal, Shanshan Ma
Deep Neural Network System Performance State Estimation Distribution System Phasor Measurement Unit System State Estimation Experimental Verification

November 7, 2023

A Method to Improve the Performance of Reinforcement Learning Based on the Y Operator for a Class of Stochastic Differential Equation-Based Child-Mother Systems
Cheng Yin, Yi Chen
Reinforcement Learning System Performance Practical Method Optimal Control Stochastic Differential Equation

November 4, 2023

Enhancing the Performance of Pneu-net Actuators Using a Torsion Resistant Strain Limiting Layer
Ian Sullivan Good, Srivatsan Balaji, Jeffrey Ian Lipton
System Performance Multi Layer Soft Robotics Soft Gripper Pneumatic Actuator Thin Shell Soft Robotic Grippers

November 2, 2023

Predicting Question-Answering Performance of Large Language Models through Semantic Consistency
Ella Rabinovich, Samuel Ackerman, Orna Raz, Eitan Farchi, Ateret Anaby-Tavor
Language Model Human Prediction System Performance Semantic Consistency

October 31, 2023

Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building
Omar Momen, David Arps, Laura Kallmeyer
Language Model System Performance Implicit Structure

October 27, 2023

October 26, 2023

Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance
Donald Loveland, Rajmonda Caceres
Graph Neural Network Technical Challenge System Performance Non Rigid Editing Network Design Graph Edit Distance Gradient Manipulation

System Performance

Papers

The performance of multiple language models in identifying offensive language on social media

On the Performance of Temporal Difference Learning With Neural Networks

Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis

Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge

Empowering COVID-19 Detection: Optimizing Performance Through Fine-Tuned EfficientNet Deep Learning Architecture

Improving performance of heart rate time series classification by grouping subjects

Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations

SSB: Simple but Strong Baseline for Boosting Performance of Open-Set Semi-Supervised Learning

IncepSE: Leveraging InceptionTime's performance with Squeeze and Excitation mechanism in ECG analysis

Breaking Boundaries: Balancing Performance and Robustness in Deep Wireless Traffic Forecasting

Performance of Machine Learning Classification in Mammography Images using BI-RADS

Eval-GCSC: A New Metric for Evaluating ChatGPT's Performance in Chinese Spelling Correction

Analytical Verification of Performance of Deep Neural Network Based Time-Synchronized Distribution System State Estimation

A Method to Improve the Performance of Reinforcement Learning Based on the Y Operator for a Class of Stochastic Differential Equation-Based Child-Mother Systems

Enhancing the Performance of Pneu-net Actuators Using a Torsion Resistant Strain Limiting Layer

Predicting Question-Answering Performance of Large Language Models through Semantic Consistency

Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building

Enhancing the Performance of a Biomimetic Robotic Elbow-and-Forearm System Through Bionics-Inspired Optimization

DELPHI: Data for Evaluating LLMs' Performance in Handling Controversial Issues

Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance