Zengrui Jin

Toward Extremely Low-Bit and Multi-Precision Conformer and Speech Foundation Model Quantization

Model quantization facilitates Automatic Speech Recognition (ASR) deployment on resource-constrained devices, yet existing methods suffer from severe accuracy loss below 4 bits, redundant storage for multiple precisions, and limited applicability across training paradigms. We address these challenges with two methods t...

Towards general auditory intelligence for machine listening and speaking

FSA-GRPO: Teaching Auditory LLMs to Use Few-shot Demonstrations

This work introduces Few-Shot Aware GRPO (FSA-GRPO), an RL-based post-training recipe that uses a specially designed reward to encourage the model to leverage few-shot demonstrations, thereby strengthening its few-shot adaptation ability.