Papers by Rahul Kejriwal

2 papers
A Large-scale Evaluation of Neural Machine Transliteration for Indic Languages (2021.eacl-main)

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Challenge: We analyze multilingual transliteration for Indic languages using scripts derived from the ancient Brahmi script.
Approach: They propose a multilingual training recipe for Indic languages that utilizes orthographic similarity between English and Indic.
Outcome: The proposed training recipe improves multilingual transliteration for Indic languages.
CharSpan: Utilizing Lexical Similarity to Enable Zero-Shot Machine Translation for Extremely Low-resource Languages (2024.eacl-short)

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Challenge: Existing models for ELRLs lack parallel corpora and monolingual corporata . authors propose novel character-span noise argumentation model to facilitate cross-lingual transfer .
Approach: They propose a character-span noise argumentation model to facilitate cross-lingual transfer . they use character-size noise argumentations to regularize training data of HRL .
Outcome: The proposed model outperforms baselines on closely related HRL-ELRL pairs from three different language families.

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