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Found 4 papers, 2 papers with code
FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity
%on how to exploit strong convexity to further improve the convergence rate of AdaBelief.
No Answer is Better Than Wrong Answer: A Reflection Model for Document Level Machine Reading Comprehension
The Natural Questions (NQ) benchmark set brings new challenges to Machine Reading Comprehension: the answers are not only at different levels of granularity (long and short), but also of richer types (including no-answer, yes/no, single-span and multi-span).
Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering
While question answering (QA) with neural network, i. e. neural QA, has achieved promising results in recent years, lacking of large scale real-word QA dataset is still a challenge for developing and evaluating neural QA system.
Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation
On the WMT'14 English-to-French task, we achieve BLEU=37. 7 with a single attention model, which outperforms the corresponding single shallow model by 6. 2 BLEU points.
Ranked #37 on
Machine Translation
on WMT2014 English-French
