🎯 TL;DR: State-of-the-art paired encoder and decoder models (17M-1B params) trained identically for fair comparison with open data. Encoders beat ModernBERT. Decoders beat Llama 3.2/SmolLM2. These ...

A deep learning-based Machine Translation system that translates text from one language to another using an Encoder-Decoder architecture with attention mechanism. Built using TensorFlow, Keras, and ...

What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...

Abstract: In the realm of integrated circuit verification, IR drop analysis plays a crucial role. Recent advancements in machine learning (ML) significantly enhance its efficiency, yet many current ...

Abstract: Address event representation (AER) object recognition task has attracted extensive attention in neuromorphic vision processing. The spike-based and event-driven computation inherent in the ...

Hold on - AI and Deep Learning are that easy? Of course, it’s not that easy: There is a big difference between using a model and training a model. Before we can reach the point where we have such a ...