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.
789papers
Papers - Page 16
October 21, 2024
October 19, 2024
October 18, 2024
October 17, 2024
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
IterSelectTune: An Iterative Training Framework for Efficient Instruction-Tuning Data Selection
FTSmartAudit: A Knowledge Distillation-Enhanced Framework for Automated Smart Contract Auditing Using Fine-Tuned LLMs
Data Driven Environmental Awareness Using Wireless Signals
October 15, 2024
Safety Filtering While Training: Improving the Performance and Sample Efficiency of Reinforcement Learning Agents
Efficient, Accurate and Stable Gradients for Neural ODEs
PaSTe: Improving the Efficiency of Visual Anomaly Detection at the Edge
GS^3: Efficient Relighting with Triple Gaussian Splatting
Using Zone Inflation and Volume Transfer to Design a Fabric-based Pneumatic Exosuit with both Efficiency and Wearability
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
Motion Planning for Automata-based Objectives using Efficient Gradient-based Methods