Fetching the paper…
Reading the bibliography…
We propose a large scale semantic parsing dataset focused on instruction-driven communication with an agent in Minecraft.
Evaluation of spoken language systems: The atis domain
Patti J Price. 1990 · 1990
Earlier work this paper cites.
Using multiple clause constructors in inductive logic programming for semantic parsing
Lappoon R Tang and Raymond J Mooney. 2001 · 2001
Earlier work this paper cites.
Chameleons in imagined conversations: A new approach to understanding coordination of linguistic style in dialogs
Cristian Danescu-Niculescu-Mizil and Lillian Lee. 2011 · 2011
Earlier work this paper cites.
Understanding natural language commands for robotic navigation and mobile manipulation
Stefanie Tellex, Thomas Kollar, Steven Dickerson, Matthew R Walter, Ashis Gopal Banerjee, Seth Teller, and Nicholas Roy. 2011 · 2011
Earlier work this paper cites.
Weakly supervised learning of semantic parsers for mapping instructions to actions
Yoav Artzi and Luke Zettlemoyer. 2013 · 2013
Earlier work this paper cites.
Large-scale semantic parsing via schema matching and lexicon extension
Qingqing Cai and Alexander Yates. 2013 · 2013
Earlier work this paper cites.
Toward interactive grounded language acqusition
Thomas Kollar, Jayant Krishnamurthy, and Grant P Strimel. 2013 · 2013
Earlier work this paper cites.
Learning to parse natural language commands to a robot control system
Cynthia Matuszek, Evan Herbst, Luke Zettlemoyer, and Dieter Fox. 2013 · 2013
Earlier work this paper cites.
Learning phrase representations using RNN encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Learning to interpret natural language commands through human-robot dialog
Jesse Thomason, Shiqi Zhang, Raymond J Mooney, and Peter Stone. 2015 · 2015
Earlier work this paper cites.
Building a semantic parser overnight
Yushi Wang, Jonathan Berant, and Percy Liang. 2015 · 2015
Earlier work this paper cites.
Language to logical form with neural attention
Li Dong and Mirella Lapata. 2016 · 2016
Cited alongside, same era.
Data recombination for neural semantic parsing
Robin Jia and Percy Liang. 2016 · 2016
Cited alongside, same era.
The malmo platform for artificial intelligence experimentation
Matthew Johnson, Katja Hofmann, Tim Hutton, and David Bignell. 2016 · 2016
Cited alongside, same era.
Neural symbolic machines: Learning semantic parsers on freebase with weak supervision
Chen Liang, Jonathan Berant, Quoc Le, Kenneth D Forbus, and Ni Lao. 2016 · 2016
Cited alongside, same era.
Learning a natural language interface with neural programmer
Arvind Neelakantan, Quoc V Le, Martin Abadi, Andrew McCallum, and Dario Amodei. 2016 · 2016
Where is misty? interpreting spatial descriptors by modeling regions in space
Nikita Kitaev and Dan Klein. 2017 · 2017
Later among the works it cites.
Opennmt: Open-source toolkit for neural machine translation
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander M. Rush. 2017 · 2017
Later among the works it cites.
Zero-shot task generalization with multi-task deep reinforcement learning
Junhyuk Oh, Satinder Singh, Honglak Lee, and Pushmeet Kohli. 2017 · 2017
Later among the works it cites.
Hierarchical and interpretable skill acquisition in multi-task reinforcement learning
Tianmin Shu, Caiming Xiong, and Richard Socher. 2017 · 2017
Later among the works it cites.
A deep hierarchical approach to lifelong learning in minecraft
Chen Tessler, Shahar Givony, Tom Zahavy, Daniel J Mankowitz, and Shie Mannor. 2017 · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Control of memory, active perception, and action in minecraft
Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, and Honglak Lee. 2016 · 2016
Cited alongside, same era.
Programming with a differentiable forth interpreter
Sebastian Riedel, Matko Bosnjak, and Tim Rocktäschel. 2016 · 2016
Cited alongside, same era.
Fighting zombies in minecraft with deep reinforcement learning
Hiroto Udagawa, Tarun Narasimhan, and Shim-Young Lee. 2016 · 2016
Cited alongside, same era.
Learning language games through interaction
Sida I Wang, Percy Liang, and Christopher D Manning. 2016 · 2016
Cited alongside, same era.
Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
Cited alongside, same era.
From language to programs: Bridging reinforcement learning and maximum marginal likelihood
Kelvin Guu, Panupong Pasupat, Evan Zheran Liu, and Percy Liang. 2017 · 2017
Cited alongside, same era.
Naturalizing a programming language via interactive learning
Sida I Wang, Samuel Ginn, Percy Liang, and Christoper D Manning. 2017 · 2017
Later among the works it cites.
Seq2sql: Generating structured queries from natural language using reinforcement learning
Victor Zhong, Caiming Xiong, and Richard Socher. 2017 · 2017
Later among the works it cites.
Deep reinforcement learning with model learning and monte carlo tree search in minecraft
Stephan Alaniz. 2018 · 2018
Later among the works it cites.
How players speak to an intelligent game character using natural language messages
Fraser Allison, Ewa Luger, and Katja Hofmann. 2018 · 2018
Later among the works it cites.
The alexa meaning representation language
Thomas Kollar, Danielle Berry, Lauren Stuart, Karolina Owczarzak, Tagyoung Chung, Lambert Mathias, Michael Kayser, Bradford Snow, and Spyros Matsoukas. 2018 · 2018
Later among the works it cites.
Neural-symbolic vqa: Disentangling reasoning from vision and language understanding
Kexin Yi, Jiajun Wu, Chuang Gan, Antonio Torralba, Pushmeet Kohli, and Josh Tenenbaum. 2018 · 2018
Later among the works it cites.