Research
Advancing how machines understand and generate human language across speech, text, and translation.
Creators, players and AI models collaboratively build and evolve games over time In this project, we explore how game creators, players and generative AI models can collaboratively build and continually evolve games over time. We…
Speaker: Benjamin StahlHost: Hannes Gamper In this talk, we explore advancements in computational models for speech quality assessment. Self-supervised learning models have emerged as powerful front-ends, outperforming supervised-only models. However, their large size renders them…
Much of recent progress for natural language generation (NLG) has been in the context of English and, in general, high resource languages, however, Indian languages have yet to see similar paradigm shifts despite their speaking…
Million-Tokens Prompt Inference for Long-context LLMs MInference 1.0 leverages the dynamic sparse nature of LLMs’ attention, which exhibits some static patterns, to speed up the pre-filling for long-context LLMs. It first determines offline which sparse pattern…
