Papers by Abhishek Purushothama

2 papers
Syntax as a Rosetta Stone: Universal Dependencies for In-Context Coptic Translation (2026.findings-acl)

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Challenge: Existing work using bilingual dictionaries to support inference for vocabulary items is lacking for low-resource languages.
Approach: They propose to use universal dependency parses of input sentences to augment in-context learning prompts for low resource machine translation for the Coptic language.
Outcome: The proposed approach achieves state-of-the-art results for the Coptic language.
Getting The Most Out of Your Training Data: Exploring Unsupervised Tasks for Morphological Inflection (2024.emnlp-main)

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Challenge: Pre-trained transformers have been shown to be effective in many natural language tasks, but are under-explored for character-level sequence to sequence tasks.
Approach: They propose to use pre-trained transformers for character-level morphological inflection in several languages to train models for unsupervised tasks.
Outcome: The proposed model outperforms the best two shared tasks on morphological inflection and graphemeto-phoneme conversion benchmarks.

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