FSA-GRPO: Teaching Auditory LLMs to Use Few-Shot Demonstrations
Few-shot prompting provides an effective way to adapt auditory large language models to low-resource tasks such as children's speech recognition. However, most auditory large language models are not explicitly trained to perform inference in this demonstration-conditioned format, limiting the extent to which they can benefit from In-Context Learning (ICL). To address this limitation, we introduce 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. Notably, training with only 2k high-resource adult ASR utterances improves the ...
| Authors | Haolong Zheng, Siyin Wang, Xulin Fan et al. |
|---|---|
| Primary category | eess.AS |
| Published | 26 May 2026 |
| Last updated at source | 29 August 2026 |
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