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
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris Papailiopoulos, Kangwook Lee
PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection
Linfeng Zhang, Runpei Dong, Hung-Shuo Tai, Kaisheng Ma