Abstract: Problem transformation-based multiobjective evolutionary algorithms (MOEAs) face the risk of losing optimal solutions when transforming a large-scale multiobjective optimization problem into ...

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Abstract: Over the past decades, extensive research has been conducted on adversarial attacks and defense mechanisms in deep learning, particularly in real-world applications such as autonomous ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

oLLM is a lightweight Python library built on top of Huggingface Transformers and PyTorch and runs large-context Transformers on NVIDIA GPUs by aggressively offloading weights and KV-cache to fast ...

SAN DIEGO — Darwin, a python involved in the "Read to a Reptile" program at the Ocean Beach Library was found on Friday after disappearing two days ago. "I was really getting very worried. I wasn't ...

A new evolutionary technique from Japan-based AI lab Sakana AI enables developers to augment the capabilities of AI models without costly training and fine-tuning processes. The technique, called ...

Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...

The library supports custom instances, among other capabilities. Announced June 26, the Data Commons Python library can be used to explore the Data Common knowledge graph and retrieve statistical data ...

The Python Context Library provides powerful, thread-safe context management capabilities for Python applications. It offers a flexible and intuitive API for managing contextual data across different ...