Abstract Natural language provides an intuitive and powerful interface to access knowledge at scale. Modern language systems draw information from two rich knowledge sources: (1) information stored in their parameters during massive pretraining and (2)[…]
Abstract The speech field is evolving to solve more challenging scenarios, such as multi-channel recordings with multiple simultaneous talkers. Given the many types of microphone setups out there, we present the UniX-Encoder. It’s a universal[…]
Abstract Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains. However, it is still very challenging to build highly-reliable applications with LLMs that support specialized use cases. LLMs trained on web data often[…]
Abstract Most machine translation systems operate on the sentence-level while humans write and translate within a given context. Operating on individual sentences forces error-prone sentence segmentation into the machine translation pipeline. This limits the upper-bound[…]
Abstract As artificial intelligence (AI) continues to rapidly expand into existing healthcare infrastructure – e.g., clinical decision support, administrative tasks, and public health surveillance – it is perhaps more important than ever to reflect on[…]
Abstract I discuss the application of Foundation Models in Astronomy through the collaborative efforts of the UniverseTBD consortium with a mission to democratize Science for everyone. One of our key objectives is to overcome the[…]
Abstract We introduce STAR (Stream Transduction with Anchor Representations), a novel Transformer-based model designed for efficient sequence-to-sequence transduction over streams. STAR dynamically segments input streams to create compressed anchor representations, achieving nearly lossless compression (12x)[…]