Latest Articles for Performance

Sharing experiences to improve future robotic development.

Explore how self-modeling enhances machine efficiency and teamwork.

Debloating software enhances speed and security by removing unnecessary code.

This article reviews the reliability of models in analyzing visual data.

Evaluating the impact of decoding strategies on LLM performance.

A new method using diffusion models improves chip placement efficiency and effectiveness.

Tiled Bit Networks optimize deep learning models for better efficiency and performance.

This article introduces minimax quantiles for better statistical estimates.

A new approach to reduce tail latency in applications using a dynamic thread pool.

This paper analyzes the importance of auto-tuning for AMD GPUs in high-performance computing.

Combining LLMs and Prolog improves reasoning in text generation.

DropKAN improves KANs' performance by addressing Dropout issues.

Analyzing the importance and difficulties of assessing multimodal AI models.

Techniques for better maintenance and performance of static analysis tools.

This study highlights STR improvements using RoBERTa across languages.

This article examines how configural processing aids in object recognition.

A new framework estimates how deep learning models perform on various GPUs.

Discover how vocabulary size influences the performance of large language models.

A study on optimizing RL agents through careful selection of training instances.

Methods for optimizing performance in large language model training and inference.

Smaller models tailored for specific fields, like medicine, show great potential.

Explore how Cellular Automata reveal employee dynamics and influence performance in organizations.

A new model enhances AI's grasp of video game content.

New method improves classification accuracy and adaptability through error detection.

This study analyzes the performance of neural network circuits and their reliability.

Combining matrix product states and Chebyshev polynomials for efficient function approximation.

A method to speed up training of multimodal large language models while improving performance.

Explore how microstructure influences the performance of hyperelastic materials.

A new benchmark improves models' understanding of long videos and language.

A new approach to assess model performance and knowledge retention.

Exploring the shift from dot products to learned similarities for better retrieval.

Study reveals how extra thinking steps improve RNN performance in Sokoban.

SCALL adjusts embedding sizes for improved recommendations using less memory.

This method enhances prompt creation for large language models, improving overall performance.

Examining the challenges of fairness in AI for medical imaging.

Analyzing the effectiveness of RAG and long-context LLMs in processing text.

New actuator design enhances underwater robot capabilities by mimicking fish fins.

Learn how agents influence each other in work settings through motivation and contracts.

A novel approach to improve multimodal learning with missing data.

This study examines constraints for the repeated ReLU function in neural networks.