Papers by Beom Jin Kang

1 papers
GenPTQ: Green Post-Training Quantization for Large-Scale ASR Models with Mixed-Precision Bit Allocation (2025.findings-emnlp)

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Challenge: Large-scale models with high memory and computation demands face significant challenges for deployment.
Approach: They propose a weight-only quantization method that optimizes for weights and QAT to restore accuracy.
Outcome: The proposed method achieves 89.1% model size reduction with only 0.8% increase in WER and completes optimization in just 15 seconds.

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