Fetching the paper…
Reading the bibliography…
The dominant paradigm for neural text generation is left-to-right decoding from autoregressive language models.
A formal basis for the heuristic determination of minimum cost paths
Peter E. Hart, Nils J. Nilsson, and Bertram Raphael. 1968 · 1968
Earlier work this paper cites.
First Results on the Effect of Error in Heuristic Search
Ira Pohl. 1970 · 1970
Earlier work this paper cites.
Heuristics - intelligent search strategies for computer problem solving
Judea Pearl. 1984 · 1984
Earlier work this paper cites.
Depth-first iterative-deepening: An optimal admissible tree search
Richard E Korf. 1985 · 1985
Earlier work this paper cites.
An efficient a* search algorithm for statistical machine translation
Franz Josef Och, Nicola Ueffing, and Hermann Ney. 2001 · 2001
Earlier work this paper cites.
BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
A* parsing: Fast exact Viterbi parse selection
Dan Klein and Christopher D. Manning. 2003 · 2003
Earlier work this paper cites.
Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard Hovy. 2003 · 2003
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
Earlier work this paper cites.
Efficient search for inversion transduction grammar
Hao Zhang and Daniel Gildea. 2006 · 2006
Earlier work this paper cites.
Approximate factoring for A* search
Aria Haghighi, John DeNero, and Dan Klein. 2007 · 2007
Earlier work this paper cites.
Cube pruning as heuristic search
Mark Hopkins and Greg Langmead. 2009 · 2009
Earlier work this paper cites.
Learning semantic correspondences with less supervision
Percy Liang, Michael Jordan, and Dan Klein. 2009 · 2009
Earlier work this paper cites.
Efficient CCG parsing: A* versus adaptive supertagging
Michael Auli and Adam Lopez. 2011 · 2011
Earlier work this paper cites.
Text alignment for real-time crowd captioning
Iftekhar Naim, Daniel Gildea, Walter Lasecki, and Jeffrey P Bigham. 2013 · 2013
Earlier work this paper cites.
Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
Earlier work this paper cites.
Spice: Semantic propositional image caption evaluation
Peter Anderson, Basura Fernando, Mark Johnson, and Stephen Gould. 2016 · 2016
Earlier work this paper cites.
Sequence-to-sequence generation for spoken dialogue via deep syntax trees and strings
Ondřej Dušek and Filip Jurčíček. 2016 · 2016
Cited alongside, same era.
Global neural CCG parsing with optimality guarantees
Kenton Lee, Mike Lewis, and Luke Zettlemoyer. 2016 · 2016
Cited alongside, same era.
A corpus and cloze evaluation for deeper understanding of commonsense stories
Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, and James Allen. 2016 · 2016
Cited alongside, same era.
Multi-domain neural network language generation for spoken dialogue systems
Tsung-Hsien Wen, Milica Gašić, Nikola Mrkšić, Lina M. Rojas-Barahona, Pei-Hao Su, David Vandyke, and Steve Young. 2016 · 2016
Cited alongside, same era.
Guided open vocabulary image captioning with constrained beam search
Peter Anderson, Basura Fernando, Mark Johnson, and Stephen Gould. 2017 · 2017
Cited alongside, same era.
Plug and play language models: A simple approach to controlled text generation
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu. 2019 · 2019
Later among the works it cites.
Training neural machine translation to apply terminology constraints
Georgiana Dinu, Prashant Mathur, Marcello Federico, and Yaser Al-Onaizan. 2019 · 2019
Later among the works it cites.
Improved lexically constrained decoding for translation and monolingual rewriting
J. Edward Hu, Huda Khayrallah, Ryan Culkin, Patrick Xia, Tongfei Chen, Matt Post, and Benjamin Van Durme. 2019 · 2019
Later among the works it cites.
Comparison of diverse decoding methods from conditional language models
Daphne Ippolito, Reno Kriz, João Sedoc, Maria Kustikova, and Chris Callison-Burch. 2019 · 2019
Later among the works it cites.
Cgmh: Constrained sentence generation by metropolis-hastings sampling
Ning Miao, Hao Zhou, Lili Mou, Rui Yan, and Lei Li. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shujian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, Lucia Specia, and Marco Turchi. 2017 · 2017
Cited alongside, same era.
Guiding neural machine translation decoding with external knowledge
Rajen Chatterjee, Matteo Negri, Marco Turchi, Marcello Federico, Lucia Specia, and Frédéric Blain. 2017 · 2017
Cited alongside, same era.
Lexically constrained decoding for sequence generation using grid beam search
Chris Hokamp and Qun Liu. 2017 · 2017
Cited alongside, same era.
Toward controlled generation of text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017 · 2017
Cited alongside, same era.
Challenges in data-to-document generation
Sam Wiseman, Stuart Shieber, and Alexander Rush. 2017 · 2017
Cited alongside, same era.
Recurrent neural networks as weighted language recognizers
Yining Chen, Sorcha Gilroy, Andreas Maletti, Jonathan May, and Kevin Knight. 2018 · 2018
Cited alongside, same era.
Findings of the E2E NLG Challenge
Ondřej Dušek, Jekaterina Novikova, and Verena Rieser. 2018 · 2018
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Later among the works it cites.
Pragmatically informative text generation
Sheng Shen, Daniel Fried, Jacob Andreas, and Dan Klein. 2019 · 2019
Later among the works it cites.
Language models are few-shot learners
T. Brown, B. Mann, Nick Ryder, Melanie Subbiah, J. Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, G. Krüger, T. Henighan, R. Child, Aditya Ramesh, D. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, E. Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, J. Clark, Christopher Berner, Sam McCandlish, A. Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Later among the works it cites.
KGPT: Knowledge-grounded pre-training for data-to-text generation
Wenhu Chen, Yu Su, Xifeng Yan, and William Yang Wang. 2020b · 2020
Later among the works it cites.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
Later among the works it cites.
Commongen: A constrained text generation challenge for generative commonsense reasoning
Bill Yuchen Lin, Ming Shen, Wangchunshu Zhou, Pei Zhou, Chandra Bhagavatula, Yejin Choi, and Xiang Ren. 2020 · 2020
Later among the works it cites.
Best-first beam search
Clara Meister, Tim Vieira, and Ryan Cotterell. 2020 · 2020
Later among the works it cites.
Backpropagation-based decoding for unsupervised counterfactual and abductive reasoning
Lianhui Qin, Vered Shwartz, Peter West, Chandra Bhagavatula, Jena D Hwang, Ronan Le Bras, Antoine Bosselut, and Yejin Choi. 2020 · 2020
Later among the works it cites.
Language generation via combinatorial constraint satisfaction: A tree search enhanced Monte-Carlo approach
Maosen Zhang, Nan Jiang, Lei Li, and Yexiang Xue. 2020 · 2020
Later among the works it cites.
Opportunistic decoding with timely correction for simultaneous translation
Renjie Zheng, Mingbo Ma, Baigong Zheng, Kaibo Liu, and Liang Huang. 2020 · 2020
Later among the works it cites.
Machine translation decoding beyond beam search
Rémi Leblond, Jean-Baptiste Alayrac, Laurent Sifre, Miruna Pislar, Jean-Baptiste Lespiau, Ioannis Antonoglou, Karen Simonyan, and Oriol Vinyals. 2021 · 2021
Closest in time.
NeuroLogic decoding: (un)supervised neural text generation with predicate logic constraints
Ximing Lu, Peter West, Rowan Zellers, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
Closest in time.
Reflective decoding: Beyond unidirectional generation with off-the-shelf language models
Peter West, Ximing Lu, Ari Holtzman, Chandra Bhagavatula, Jena D. Hwang, and Yejin Choi. 2021 · 2021
Closest in time.