2 papers
cs.CL2024
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
Sotiris Anagnostidis, Dario Pavllo, Luca Biggio +3
Autoregressive Transformers adopted in Large Language Models (LLMs) are hard to scale to long sequences. Despite several works trying to reduce their computational cost, most of LL…
cs.SD2024
FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control
Dimitri von Rütte, Luca Biggio, Yannic Kilcher +1
Generating music with deep neural networks has been an area of active research in recent years. While the quality of generated samples has been steadily increasing, most methods ar…