Papers by Jushaan Kalra

1 papers
JobXMLC: EXtreme Multi-Label Classification of Job Skills with Graph Neural Networks (2023.findings-eacl)

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Challenge: Existing approaches to predict missing skills are limited to contextual modelling and do not exploit inter-relational structures like job-job and job-skill relationships.
Approach: They propose a skill prediction framework that exploits structural relationships to predict missing skills using job descriptions.
Outcome: The proposed framework outperforms the state-of-the-art approaches by 6% in precision and 3% in recall on real-world recruitment datasets.

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