3 accepted papers
Existing time series foundation models (TSFMs), often based on transformer variants, lack adaptability to different sampling rates, struggle with generalization across varying context and target lengths and are computationally inefficient. We introduce FlowState, a novel TSFM architecture that achie…
Human capabilities in understanding visual relations are far superior to those of AI systems, especially for previously unseen objects. For example, while AI systems struggle to determine whether two such objects are visually the same or different, humans can do so with ease. Active vision theories…
Automatic speech recognition systems (ASR), such as the recurrent neural network transducer (RNN-T), have reached close to human-like performance and are deployed in commercial applications. However, their core operations depart from the powerful biological counterpart, the human brain. On the other…