Papers by Andrey Malinin

2 papers
Uncertainty Measures in Neural Belief Tracking and the Effects on Dialogue Policy Performance (2021.emnlp-main)

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Challenge: Neural dialogue belief trackers that take uncertainty into account are often overconfident in their decisions and therefore less robust.
Approach: They propose to use different uncertainty measures in neural belief tracking to integrate uncertainty into the feature space of the policy and train policies through interaction with a user simulator.
Outcome: The proposed approach improves both performance and robustness of the downstream dialogue policy.
Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search Degradation (2021.emnlp-main)

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Challenge: Neural Machine Translation suffers from a beam-search problem after a certain point, especially for long sentences.
Approach: They propose a data augmentation technique that concatenates several sentences from the original dataset to make a long training example.
Outcome: The proposed technique significantly reduces degradation with growing beam size and improves translation quality on the IWSTL15 En-Vi, IWStl17 En-Fr, and WMT14 En-De datasets.

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