🎯 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 ...

The encoder-decoder transformer is one of the most influential architectures in natural language processing (NLP) and various machine learning applications. It revolutionized tasks such as machine ...

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 ...

We note that our work focuses on architectural comparisons rather than competing with recent SLM developments (e.g., SmolLM, MobileLLM). Our analysis isolates the fundamental advantages of ...

In the Transformer architecture, both the encoder and decoder play crucial roles in processing input sequences and generating output sequences, respectively. Let's break down how each component works: ...

Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

Colorectal cancer (CRC) is a form of cancer that impacts the large intestine, constituting one of the most severe and most common forms of cancer. 5-year survival rates depend on a variety of ...

Automatic segmentation of anatomical structures (such as organs) and lesion regions in medical images has become a critical task in medical image analysis and is widely used in clinical diagnosis and ...

In this paper, we introduce the world’s first 8K 120-Hz video real-time encoder and decoder that complies with ARIB STD-B32 1) . We evaluated the coding efficiency and demonstrated that 8K 120-Hz ...

VVenC and VVdeC are open-source software H.266/VCC video encoder and decoder respectively that are optimized to use SIMD instructions on x86 (SSE42/SIMDe and AVX2) and Arm, and the decoder runs on ...