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Found 3 papers, 1 papers with code
Can Perplexity Predict Fine-Tuning Performance? An Investigation of Tokenization Effects on Sequential Language Models for Nepali
To reduce this gap we used 6 different tokenization schemes to pretrain relatively small language models in Nepali and used the representations learned to finetune on several downstream tasks.
Contextual Spelling Correction with Language Model for Low-resource Setting
The task of Spell Correction(SC) in low-resource languages presents a significant challenge due to the availability of only a limited corpus of data and no annotated spelling correction datasets.
Cross-modal Contrastive Learning with Asymmetric Co-attention Network for Video Moment Retrieval
Video moment retrieval is a challenging task requiring fine-grained interactions between video and text modalities.
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