Papers by Gourab Kundu

2 papers
Neural Cross-Lingual Coreference Resolution And Its Application To Entity Linking (P18-2)

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Challenge: a cross-lingual coreference model is based on multi-lingual embeddings and language independent features.
Approach: They propose a crosslingual coreference model that builds on multi-lingual embeddings and language independent features.
Outcome: The proposed model outperforms the existing models on Chinese and Spanish test sets.
Normalized Contrastive Learning for Text-Video Retrieval (2022.emnlp-main)

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Challenge: Cross-modal contrastive learning suffers from incorrect normalization of the sum retrieval probabilities of each text or video instance.
Approach: They propose a normalized contrastive learning algorithm that normalizes the sum retrieval probabilities of each instance so that every text and video instance is fairly represented.
Outcome: Empirical results show that NCL brings significant gains in text-video retrieval on different model architectures without any architecture engineering.

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