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A strength coefficient that interpolates between uncalibrated and fully equalized attention, together with an efficient implementation that reduces peak calibration memory overhead from 5-7 GiB to under 1 MiB, and a variant that preserves the pooling token's self-attention mass and redistributes only the remaining mass...
Results show that modern LLM-assisted OCR post-correction systems can significantly improve OCR quality, but performance varies across datasets, languages, and noise levels.
A large-scale empirical study across a diverse set of embedding models and 275+ languages spanning three parallel datasets, exposing persistent gaps in cross-lingual semantic representation that track language prevalence in training resources and subword tokenization.
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