October 8, 2021

Title: Exploring a Sampling-based Alternative to Beam Search
Time: Oct 8, 2021 05:00 PM (17:00) Universal Time UTC
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In this talk, I will discuss the potential of Minimum Bayes Risk (MBR) decoding — a sampling-based decoding algorithm — to replace beam search in machine translation. Beam search is the de-facto standard decoding algorithm for many language generation problems. However, recent work has found that beam search itself causes or exacerbates well-known biases in machine translation. Minimum Bayes Risk (MBR) decoding was suggested as an alternative algorithm that does not search for the highest-scoring translation but operates on a pool of samples. I will highlight that MBR does not alleviate well-known biases in machine translation, but, interestingly, increases the robustness to noise in the training data and to domain shift.
Mathias is a post-doc and lecturer at the University of Zurich. His current main interests are 1) the meta-sciences of scientific integrity, methodology and reproducibility applied to machine translation, 2) decoding algorithms and 3) sign language translation. In his personal life he is a father of two and a passionate musician.

Please find more information about him here: cl.uzh.ch/mmueller

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