Fetching the paper…
Reading the bibliography…
Beam search and exhaustive search are two extreme ends of text decoding algorithms with respect to the search depth.
A Probabilistic Earley Parser as a Psycholinguistic Model
Hale, J. 2001 · 2001
Earlier work this paper cites.
Bleu: a Method for Automatic Evaluation of Machine Translation
Papineni, K.; Roukos, S.; Ward, T.; and Zhu, W.-J. 2002 · 2002
Earlier work this paper cites.
ROUGE: A Package for Automatic Evaluation of Summaries
Lin, C.-Y. 2004 · 2004
Earlier work this paper cites.
Probabilistic models of word order and syntactic discontinuity
Levy, R. 2005 · 2005
Earlier work this paper cites.
Speakers optimize information density through syntactic reduction
Levy, R.; and Jaeger, T. F. 2006 · 2006
Earlier work this paper cites.
Findings of the 2014 Workshop on Statistical Machine Translation
Bojar, O.; Buck, C.; Federmann, C.; Research, M.; Haddow, B.; Koehn, P.; Edinburgh, J. .; Leveling, J.; Monz, C.; Pecina, P.; Post, M.; Saint-Amand, H.; Google, R. S.; and Specia, L. 2014 · 2014
Earlier work this paper cites.
Teaching machines to read and comprehend
Hermann, K. M.; Kocisky, T.; Grefenstette, E.; Espeholt, L.; Kay, W.; Suleyman, M.; and Blunsom, P. 2015 · 2015
Earlier work this paper cites.
A Neural Attention Model for Abstractive Sentence Summarization
Rush, A. M.; Chopra, S.; and Weston, J. 2015 · 2015
Earlier work this paper cites.
Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Wu, Y.; Schuster, M.; Chen, Z.; Le, Q. V.; Norouzi, M.; Macherey, W.; Krikun, M.; Cao, Y.; Gao, Q.; Macherey, K.; Klingner, J.; Shah, A.; Johnson, M.; Liu, X.; Łukasz Kaiser; Gouws, S.; Kato, Y.; Kudo, T.; Kazawa, H.; Stevens, K.; Kurian, G.; Patil, N.; Wang, W.; Young, C.; Smith, J.; Riesa, J.; Rudnick, A.; Vinyals, O.; Corrado, G.; Hughes, M.; and Dean, J. 2016 · 2016
Earlier work this paper cites.
Guided Open Vocabulary Image Captioning with Constrained Beam Search
Anderson, P.; Fernando, B.; Johnson, M.; and Gould, S. 2017 · 2017
Earlier work this paper cites.
Convolutional Sequence to Sequence Learning
Gehring, J.; Auli, M.; Grangier, D.; Yarats, D.; and Dauphin, Y. N. 2017 · 2017
Earlier work this paper cites.
Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
Hokamp, C.; and Liu, Q. 2017 · 2017
Earlier work this paper cites.
Six Challenges for Neural Machine Translation
Koehn, P.; and Knowles, R. 2017 · 2017
Earlier work this paper cites.
SGNMT – A Flexible NMT Decoding Platform for Quick Prototyping of New Models and Search Strategies
Stahlberg, F.; Hasler, E.; Saunders, D.; and Byrne, B. 2017 · 2017
Earlier work this paper cites.
Attention is All you Need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L. u.; and Polosukhin, I. 2017 · 2017
Earlier work this paper cites.
Recurrent Neural Networks as Weighted Language Recognizers
Chen, Y.; Gilroy, S.; Maletti, A.; May, J.; and Knight, K. 2018 · 2018
Cited alongside, same era.
Correcting Length Bias in Neural Machine Translation
Murray, K.; and Chiang, D. 2018 · 2018
Cited alongside, same era.
Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization
Narayan, S.; Cohen, S. B.; and Lapata, M. 2018 · 2018
Cited alongside, same era.
A Call for Clarity in Reporting BLEU Scores
Post, M. 2018 · 2018
Cited alongside, same era.
Diverse beam search for improved description of complex scenes
Vijayakumar, A.; Cogswell, M.; Selvaraju, R.; Sun, Q.; Lee, S.; Crandall, D.; and Batra, D. 2018 · 2018
Cited alongside, same era.
Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and Stopping Criteria for Neural Machine Translation
Best-First Beam Search
Meister, C.; Vieira, T.; and Cotterell, R. 2020 · 2020
Later among the works it cites.
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding
Welleck, S.; Kulikov, I.; Kim, J.; Pang, R. Y.; and Cho, K. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-Art Natural Language Processing
Wolf, T.; Debut, L.; Sanh, V.; Chaumond, J.; Delangue, C.; Moi, A.; Cistac, P.; Rault, T.; Louf, R.; Funtowicz, M.; Davison, J.; Shleifer, S.; von Platen, P.; Ma, C.; Jernite, Y.; Plu, J.; Xu, C.; Le Scao, T.; Gugger, S.; Drame, M.; Lhoest, Q.; and Rush, A. 2020 · 2020
Later among the works it cites.
Zhang, M.; Jiang, N.; Li, L.; and Xue, Y. 2020 · 2020
Later among the works it cites.
Incremental Beam Manipulation for Natural Language Generation
Hargreaves, J.; Vlachos, A.; and Emerson, G. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yang, Y.; Huang, L.; and Ma, M. 2018 · 2018
Cited alongside, same era.
Empirical Analysis of Beam Search Performance Degradation in Neural Sequence Models
Cohen, E.; and Beck, C. 2019 · 2019
Cited alongside, same era.
Joey NMT: A Minimalist NMT Toolkit for Novices
Kreutzer, J.; Bastings, J.; and Riezler, S. 2019 · 2019
Cited alongside, same era.
CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling
Miao, N.; Zhou, H.; Mou, L.; Yan, R.; and Li, L. 2019 · 2019
Cited alongside, same era.
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Ott, M.; Edunov, S.; Baevski, A.; Fan, A.; Gross, S.; Ng, N.; Grangier, D.; and Auli, M. 2019 · 2019
Cited alongside, same era.
On NMT Search Errors and Model Errors: Cat Got Your Tongue?
Stahlberg, F.; and Byrne, B. 2019 · 2019
Cited alongside, same era.
The Curious Case of Neural Text Degeneration
Holtzman, A.; Buys, J.; Du, L.; Forbes, M.; and Choi, Y. 2020 · 2020
Cited alongside, same era.
Machine Translation Decoding beyond Beam Search
Leblond, R.; Alayrac, J.-B.; Sifre, L.; Pislar, M.; Jean-Baptiste, L.; Antonoglou, I.; Simonyan, K.; and Vinyals, O. 2021 · 2021
Later among the works it cites.
Determinantal Beam Search
Meister, C.; Forster, M.; and Cotterell, R. 2021 · 2021
Later among the works it cites.
Revisiting the Uniform Information Density Hypothesis
Meister, C.; Pimentel, T.; Haller, P.; Jäger, L.; Cotterell, R.; and Levy, R. 2021 · 2021
Later among the works it cites.
Don’t Say What You Don’t Know: Improving the Consistency of Abstractive Summarization by Constraining Beam Search
King, D.; Shen, Z.; Subramani, N.; Weld, D. S.; Beltagy, I.; and Downey, D. 2022 · 2022
Later among the works it cites.
Beam Search: Faster and Monotonic
Lemons, S.; Linares López, C.; Holte, R. C.; and Ruml, W. 2022 · 2022
Later among the works it cites.
NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics
Lu, X.; Welleck, S.; West, P.; Jiang, L.; Kasai, J.; Khashabi, D.; Le Bras, R.; Qin, L.; Yu, Y.; Zellers, R.; Smith, N. A.; and Choi, Y. 2022 · 2022
Later among the works it cites.
Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine
Jiao, W.; Wang, W.; Huang, J.; Wang, X.; and Tu, Z. 2023 · 2023
Closest in time.
Crosslingual Generalization through Multitask Finetuning
Muennighoff, N.; Wang, T.; Sutawika, L.; Roberts, A.; Biderman, S.; Le Scao, T.; Bari, M. S.; Shen, S.; Yong, Z. X.; Schoelkopf, H.; Tang, X.; Radev, D.; Aji, A. F.; Almubarak, K.; Albanie, S.; Alyafeai, Z.; Webson, A.; Raff, E.; and Raffel, C. 2023 · 2023
Closest in time.
Faithfulness-Aware Decoding Strategies for Abstractive Summarization
Wan, D.; Liu, M.; McKeown, K.; Dreyer, M.; and Bansal, M. 2023 · 2023
Closest in time.