We have 4 of 18 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Analysis indicates that embedding representations of physical measurements are strongly influenced by superficial string similarity, and recalibration of similarity does not substantially improve the alignment.
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.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
