Yingzhi Wang

This work constructed a large-scale Arabic Speech Question-Answering (SQA) corpus comprising over 1.5 million training samples to allow instruction tuning over a broad range of core speech tasks and designed an evaluation framework featuring diverse tasks and tailored metrics.

Legacy data is only useful for upgraded robots after reaching a critical competence threshold, revealing a surprising three-phase pattern in transfer learning.