Papers by Kartikeya Badola

3 papers
DiS-ReX: A Multilingual Dataset for Distantly Supervised Relation Extraction (2022.acl-short)

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Challenge: Existing benchmarking datasets for multilingual relation extraction have been lacking .
Approach: They propose to use a new benchmark dataset to study multilingual relation extraction task by distant supervision.
Outcome: The proposed task is performed on a multilingual relation extraction dataset using an mBERT encoder.
PARE: A Simple and Strong Baseline for Monolingual and Multilingual Distantly Supervised Relation Extraction (2022.acl-short)

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Challenge: Recent approaches to distantly supervised relation extraction (DS-RE) encode each sentence in an entity-pair bag separately.
Approach: They propose a simple baseline approach where sentences of a bag are concatenated into a passage of sentences and encoded jointly using BERT.
Outcome: The proposed approach outperforms state-of-the-art models in monolingual and multilingual datasets.
Parameter-Efficient Finetuning for Robust Continual Multilingual Learning (2023.findings-acl)

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Challenge: Existing approaches to Continual Multilingual Learning (CML) are based on updating models using new data in stages.
Approach: They propose a parameter-efficient finetuning strategy to increase the number of languages on which the model improves after an update while reducing the magnitude of loss for the remaining languages.
Outcome: The proposed model improves on the languages included in the latest update while reducing the loss of performance on the remaining languages.

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