A three-stage iterative LoRA training recipe (Focus, Feed Back, Fix) is applied to Whisper-large-v3 and Qwen2-Audio, reporting WER reductions on a multilingual ASR benchmark, with the gains attributed to the iterative paradigm despite a substantial data-scale confound.
In the MLC-SLM challenge, we design a three-stage training paradigm consisting of Focus, Feed Back, and Fix Training
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ILT-Iterative LoRA Training through Focus-Feedback-Fix for Multilingual Speech Recognition
A three-stage iterative LoRA training recipe (Focus, Feed Back, Fix) is applied to Whisper-large-v3 and Qwen2-Audio, reporting WER reductions on a multilingual ASR benchmark, with the gains attributed to the iterative paradigm despite a substantial data-scale confound.