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Stereotype Detection as a Catalyst for Enhanced Bias Detection: A Multi-Task Learning Approach
Aditya Tomar, Rudra Murthy, Pushpak Bhattacharyya
Bias and stereotypes in language models can cause harm, especially in sensitive areas like content moderation and decision-making. This paper addresses bias and stereotype detectio…
Denoising-based UNMT is more robust to word-order divergence than MASS-based UNMT
Tamali Banerjee, Rudra Murthy, Pushpak Bhattacharyya
We aim to investigate whether UNMT approaches with self-supervised pre-training are robust to word-order divergence between language pairs. We achieve this by comparing two models…
Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study
Tamali Banerjee, Rudra Murthy, Pushpak Bhattacharyya
Recent advances in Unsupervised Neural Machine Translation (UNMT) have minimized the gap between supervised and unsupervised machine translation performance for closely related lan…
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages
Rudra Murthy, Anoop Kunchukuttan, Pushpak Bhattacharyya
Transfer learning approaches for Neural Machine Translation (NMT) train a NMT model on the assisting-target language pair (parent model) which is later fine-tuned for the source-ta…