Methods: We evaluated 17 encoder and decoder models using J-CaseMap, a database of approximately 20,000 Japanese case reports annotated with clinical concepts. Performance was primarily assessed using ...

Artificial intelligence detectors are increasingly used to check the veracity of content online. We ran more than 1,000 tests and found several strengths and plenty of weaknesses. By Stuart A.

T5Gemma 2 follows the same adaptation idea introduced in T5Gemma, initialize an encoder-decoder model from a decoder-only checkpoint, then adapt with UL2. In the above figure the research team show ...

A compact data format optimized for transmitting structured information to Large Language Models (LLMs) with 30-60% fewer tokens than JSON. TOON (Token-Oriented Object Notation) combines YAML's ...

Visionary has introduced three new wallplate models, including USB-C Bluetooth and Dante integration, debuting at InfoComm 2025. The DuetE5-WP-C wallplate encoder combines USB-C and HDMI inputs into a ...

Beyond tumor-shed markers: AI driven tumor-educated polymorphonuclear granulocytes monitoring for multi-cancer early detection. Clinical outcomes of a prospective multicenter study evaluating a ...

Diffusion Transformers have demonstrated outstanding performance in image generation tasks, surpassing traditional models, including GANs and autoregressive architectures. They operate by gradually ...

Abstract: In unsupervised medical image registration, encoder-decoder architectures are widely used to predict dense, full-resolution displacement fields from paired images. Despite their popularity, ...

Abstract: This paper proposes a new encoder-decoder frame-work based on Convolutional Neural Networks (CNN) for feature extraction and Long Short-Term Memory (LSTM) networks for image caption ...