(2016. 10) Diverse Beam Search
Submitted on 2016. 10
Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, Qing Sun, Stefan Lee, David Crandall and Dhruv Batra
Simple Summary
propose Diverse Beam Search(DBS), an alternative to BS that decodes a list of diverse outputs by optimizing for a diversity-augmented objective. We observe that our method finds better top-1 solutions by controlling for the exploration and exploitation of the search space -- implying that DBS is a better search algorithm. Moreover, these gains are achieved with minimal computational or memory overhead as compared to beam search.
optimize an objective that consists of two terms – the sequence likelihood under the model and a dissimilarity term that encourages beams across groups to differ.
This diversity-augmented model score is optimized in a doubly greedy manner – greedily optimizing along both time (like BS) and groups (like DivMBest).
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