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This paper proposes a resource-light algorithm to automatically assign part-of-speech tags to senses in the Al-Mawrid Arabic-English bilingual dictionary by transferring tags from English WordNet after disambiguation, achieving high accuracy with minimal cost.
This paper introduces Approximate Structured Diffusion, a method that combines conditional random fields (CRFs) with discrete diffusion for sequence labelling. It uses a CRF conditioned on noisy label sequences and approximate mean-field inference, achieving a 16.5% error reduction on POS tagging.