Tianyi Chen

Leveraging a residual learning framework to support the model training on non-ideal analog in-memory computing hardware

This paper proposes conflict-aware multi-objective training strategies for multilingual automatic speech recognition and speech translation by selectively aligning gradients from conflicting layers to enhance efficiency and performance.