25 citations · 42 across the 3 of their papers we have counts for
16 papers
Minimax and Neyman-Pearson Meta-Learning for Outlier Languages
Edoardo Maria Ponti, Rahul Aralikatte, Disha Shrivastava +2
Model-agnostic meta-learning (MAML) has been recently put forth as a strategy to learn resource-poor languages in a sample-efficient fashion. Nevertheless, the properties of these…
Itihasa: A large-scale corpus for Sanskrit to English translation
Rahul Aralikatte, Miryam de Lhoneux, Anoop Kunchukuttan +1
This work introduces Itihasa, a large-scale translation dataset containing 93,000 pairs of Sanskrit shlokas and their English translations. The shlokas are extracted from two India…
Focus Attention: Promoting Faithfulness and Diversity in Summarization
Rahul Aralikatte, Shashi Narayan, Joshua Maynez +2
Professional summaries are written with document-level information, such as the theme of the document, in mind. This is in contrast with most seq2seq decoders which simultaneously…
Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards
Rahul Aralikatte, Mostafa Abdou, Heather Lent +2
Coreference resolution and semantic role labeling are NLP tasks that capture different aspects of semantics, indicating respectively, which expressions refer to the same entity, an…
Compositional Generalization in Image Captioning
Mitja Nikolaus, Mostafa Abdou, Matthew Lamm +2
Image captioning models are usually evaluated on their ability to describe a held-out set of images, not on their ability to generalize to unseen concepts. We study the problem of…
Rewarding Coreference Resolvers for Being Consistent with World Knowledge
Rahul Aralikatte, Heather Lent, Ana Valeria Gonzalez +5
Unresolved coreference is a bottleneck for relation extraction, and high-quality coreference resolvers may produce an output that makes it a lot easier to extract knowledge triples…