@inproceedings{727f7481d609412cb43401702cc80399,
title = "What Do You Get When You Cross Beam Search with Nucleus Sampling?",
abstract = "We combine beam search with the probabilistic pruning technique of nucleus sampling to create two deterministic nucleus search algorithms for natural language generation. The first algorithm, p-exact search, locally prunes the next-token distribution and performs an exact search over the remaining space. The second algorithm, dynamic beam search, shrinks and expands the beam size according to the entropy of the candidate{\textquoteright}s probability distribution. Despite the probabilistic intuition behind nucleus search, experiments on machine translation and summarization benchmarks show that both algorithms reach the same performance levels as standard beam search.",
author = "Uri Shaham and Omer Levy",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 3rd Workshop on Insights from Negative Results in NLP, Insights 2022 ; Conference date: 26-05-2022",
year = "2022",
month = jan,
day = "1",
language = "English",
series = "Insights 2022 - 3rd Workshop on Insights from Negative Results in NLP, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "38--45",
editor = "Shabnam Tafreshi and Joao Sedoc and Anna Rogers and Aleksandr Drozd and Anna Rumshisky and Akula, {Arjun Reddy}",
booktitle = "Insights 2022 - 3rd Workshop on Insights from Negative Results in NLP, Proceedings of the Workshop",
address = "United States",
}