TARQ: Tail-Aware Reconstruction Quantization for Rare-Word Robust Automatic Speech Recognition

In three linesTARQ is a post-training quantization method for ASR that rebalances calibration toward rare words (names, numerals, domain-specific terms). Without labels or validation, it improves rare-WER across 8 backbones and 6 datasets at W4G128 without aggregate-WER regression.

Summary generated by Claude — human-verified