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cs.CL2021
Retrieval Augmentation for Deep Neural Networks
Rita Parada Ramos, Patrícia Pereira, Helena Moniz +2
Deep neural networks have achieved state-of-the-art results in various vision and/or language tasks. Despite the use of large training datasets, most models are trained by iteratin…
cs.IR2021
Assessing the Benefits of Model Ensembles in Neural Re-Ranking for Passage Retrieval
Luís Borges, Bruno Martins, Jamie Callan
Our work aimed at experimentally assessing the benefits of model ensembling within the context of neural methods for passage reranking. Starting from relatively standard neural mod…