What is the best strategy to get the best rate of change in the PID for a manipulated variable, or is there a more elegant ...

Abstract: With the continuous growth in the number of parameters of the Transformer-based pretrained language models (PLMs), particularly the emergence of large language models (LLMs) with billions of ...

A core finding of the research is that Reinforcement Learning (RL) is fundamentally more efficient than Supervised Finetuning (SFT) at extremely low parameter counts. The research team reports that ...

Abstract: This paper presents a model for spring-driven flapping foil propulsion based Autonomous Underwater Vehicle (AUV) and its trajectory control for the predefined path. The spring mimics the ...

In 1871, an entire fleet of whaling ships was caught in an Arctic ice storm and destroyed. Though few lives were lost, the damage would forever shape one of America's most distinctive commodities: oil ...

A comprehensive toolkit for fine-tuning Large Language Models using LoRA, QLoRA, SFT, DPO, and RLHF. All methods tested on NVIDIA RTX 3070 Ti Laptop (8GB VRAM).

Concept-Guided Fine-Tuning (CFT) is a framework designed to enhance the out-of-distribution robustness of ViTs. Modern ViTs often suffer reliance on spurious correlations rather than the semantic ...