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 ...

Abstract: This article studies transfer-based black-box pedestrian attacks in traffic scenes, where an attacker aims to deceive a target model by generating malicious examples using a surrogate model.

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 ...

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 ...