High Efficiency
High efficiency in various computational domains is a central research theme, aiming to minimize resource consumption (time, memory, energy) while maintaining or improving performance. Current efforts focus on developing novel algorithms and architectures, such as optimized Thompson sampling for reinforcement learning, sparse attention mechanisms for transformers, and efficient model compression techniques, to achieve this goal across diverse applications including natural language processing, computer vision, and robotics. These advancements are crucial for deploying complex AI models on resource-constrained devices and for accelerating scientific discovery in data-intensive fields.
Papers
Revitalizing Electoral Trust: Enhancing Transparency and Efficiency through Automated Voter Counting with Machine Learning
Mir Faris, Syeda Aynul Karim, Md. Juniadul Islam
Integrating Active Sensing and Rearrangement Planning for Efficient Object Retrieval from Unknown, Confined, Cluttered Environments
Junyong Kim, Hanwen Ren, Ahmed H. Qureshi
Efficient and Robust Continual Graph Learning for Graph Classification in Biology
Ding Zhang, Jane Downer, Can Chen, Ren Wang
AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
Yonggan Fu, Zhongzhi Yu, Junwei Li, Jiayi Qian, Yongan Zhang, Xiangchi Yuan, Dachuan Shi, Roman Yakunin, Yingyan Celine Lin
Systolic Arrays and Structured Pruning Co-design for Efficient Transformers in Edge Systems
Pedro Palacios, Rafael Medina, Jean-Luc Rouas, Giovanni Ansaloni, David Atienza
TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scene Understanding
Quang P. M. Pham, Khoi T. N. Nguyen, Lan C. Ngo, Dezhen Song, Truong Do, Truong Son Hy
The Effect of Scheduling and Preemption on the Efficiency of LLM Inference Serving
Kyoungmin Kim, Kijae Hong, Caglar Gulcehre, Anastasia Ailamaki
Efficient and Accurate Prompt Optimization: the Benefit of Memory in Exemplar-Guided Reflection
Cilin Yan, Jingyun Wang, Lin Zhang, Ruihui Zhao, Xiaopu Wu, Kai Xiong, Qingsong Liu, Guoliang Kang, Yangyang Kang
To Train or Not to Train: Balancing Efficiency and Training Cost in Deep Reinforcement Learning for Mobile Edge Computing
Maddalena Boscaro, Federico Mason, Federico Chiariotti, Andrea Zanella
Fast and Efficient Transformer-based Method for Bird's Eye View Instance Prediction
Miguel Antunes-García, Luis M. Bergasa, Santiago Montiel-Marín, Rafael Barea, Fabio Sánchez-García, Ángel Llamazares
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation
Anil Kag, Huseyin Coskun, Jierun Chen, Junli Cao, Willi Menapace, Aliaksandr Siarohin, Sergey Tulyakov, Jian Ren
Boosting the Efficiency of Metaheuristics Through Opposition-Based Learning in Optimum Locating of Control Systems in Tall Buildings
Salar Farahmand-Tabar, Sina Shirgir