This repository implements a Feedforward Neural Network (FFNN) in Python to classify intent from the NLU Benchmark dataset. The project focuses on understanding the learning process through manual ...

So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...

Using backpropagation to compute gradients of objective functions for optimization has remained a mainstay of machine learning. Backpropagation, or reverse-mode differentiation, is a special case ...

Abstract: Real-world systems often encounter new data over time, which leads to experiencing target domain shifts. Existing Test- Time Adaptation (TTA) methods tend to apply computationally heavy and ...

Abstract: Deep neural networks are vulnerable to adversarial examples, dictating the imperativeness to test the model’s robustness before deployment. Transfer-based attackers craft adversarial ...