Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

Microsoft launches three in-house AI models for transcription, voice, and image generation, challenging OpenAI and Google with lower-cost systems.

A research team at Georgia Tech has built what it calls the first generative AI system purpose-built for polymer design, and the models have already produced a new dielectric material that held up ...

Comorbidity—the co-occurrence of multiple diseases in a patient—complicates diagnosis, treatment, and prognosis. Understanding how diseases connect at a molecular level is crucial, especially in aging ...

Achieves superior decoding accuracy and dramatically improved efficiency compared to leading classical algorithms Ra’anana, Israel, Jan. 15, 2026 (GLOBE NEWSWIRE) -- Rail Vision Ltd. (Nasdaq: RVSN) ...

This bounty is for bringing up the Time Series Transformer model using TTNN APIs on Tenstorrent hardware (Wormhole or Blackhole). Time Series Transformer is a vanilla encoder-decoder Transformer ...

Abstract: Small object detection (SOD) given aerial images suffers from an information imbalance across different feature scales. This makes it extremely challenging to perform accurate SOD. Existing ...

We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design of ...