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Existing work in language grounding typically study single environments.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Human instruction-following with deep reinforcement learning via transfer-learning from text
Felix Hill, Sona Mokra, Nathaniel Wong, and Tim Harley · 2005
Earlier work this paper cites.
Walk the talk: Connecting language, knowledge, and action in route instructions
Matt MacMahon, Brian J. Stankiewicz, and Benjamin Kuipers · 2006
Earlier work this paper cites.
A game-theoretic approach to generating spatial descriptions
Dave Golland, Percy Liang, and Dan Klein · 2010
Earlier work this paper cites.
Learning meanings of words and constructions, grounded in a virtual game
Hilke Reckman, Jeff Orkin, and Deb Roy · 2010
Earlier work this paper cites.
Learning to interpret natural language navigation instructions from observations
David L Chen and Raymond J Mooney · 2011
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
Stephane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
Earlier work this paper cites.
Learning to win by reading manuals in a monte-carlo framework
SRK Branavan, David Silver, and Regina Barzilay · 2012
Earlier work this paper cites.
Learning semantic maps from natural language descriptions
Matthew R Walter, Sachithra Hemachandra, Bianca Homberg, Stefanie Tellex, and Seth Teller · 2013
Earlier work this paper cites.
Learning spatial-semantic representations from natural language descriptions and scene classifications
Sachithra Hemachandra, Matthew R Walter, Stefanie Tellex, and Seth Teller · 2014
Earlier work this paper cites.
Alignment-based compositional semantics for instruction following
Jacob Andreas and Dan Klein · 2015
Earlier work this paper cites.
A survey of current datasets for vision and language research
Francis Ferraro, Nasrin Mostafazadeh, Ting-Hao Huang, Lucy Vanderwende, Jacob Devlin, Michel Galley, and Margaret Mitchell · 2015
Earlier work this paper cites.
OpenAI Gym, 2016
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Modular multitask reinforcement learning with policy sketches
Jacob Andreas, Dan Klein, and Sergey Levine · 2017
Earlier work this paper cites.
Navigational instruction generation as inverse reinforcement learning with neural machine translation
Andrea F Daniele, Mohit Bansal, and Matthew R Walter · 2017
Earlier work this paper cites.
Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Earlier work this paper cites.
Grounded language learning in a simulated 3d world
Karl Moritz Hermann, Felix Hill, Simon Green, Fumin Wang, Ryan Faulkner, Hubert Soyer, David Szepesvari, Wojciech Marian Czarnecki, Max Jaderberg, Denis Teplyashin, et al · 2017
Earlier work this paper cites.
Mapping instructions and visual observations to actions with reinforcement learning
Dipendra Misra, John Langford, and Yoav Artzi · 2017
Cited alongside, same era.
Zero-shot task generalization with multi-task deep reinforcement learning
Junhyuk Oh, Satinder Singh, Honglak Lee, and Pushmeet Kohli · 2017
Cited alongside, same era.
Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
Cited alongside, same era.
Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments
Peter Anderson, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson, Niko Sünderhauf, Ian Reid, Stephen Gould, and Anton van den Hengel · 2018
Cited alongside, same era.
Learning to follow language instructions with adversarial reward induction
Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Pushmeet Kohli, and Edward Grefenstette · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Later among the works it cites.
TorchBeast: A PyTorch Platform for Distributed RL
Heinrich Küttler, Nantas Nardelli, Thibaut Lavril, Marco Selvatici, Viswanath Sivakumar, Tim Rocktäschel, and Edward Grefenstette · 2019
Later among the works it cites.
A survey of reinforcement learning informed by natural language
Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, and Tim Rocktäschel · 2019
Later among the works it cites.
Leveraging procedural generation to benchmark reinforcement learning
Karl Cobbe, Christopher Hesse, Jacob Hilton, and John Schulman · 2020
Later among the works it cites.
Room-Across-Room: Multilingual vision-and-language navigation with dense spatiotemporal grounding
Alexander Ku, Peter Anderson, Roma Patel, Eugene Ie, and Jason Baldridge · 2020
Later among the works it cites.
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Touchdown: Natural language navigation and spatial reasoning in visual street environments
Howard Chen, Alane Suhr, Dipendra Kumar Misra, Noah Snavely, and Yoav Artzi · 2018
Cited alongside, same era.
Minimalistic gridworld environment for OpenAI Gym
Maxime Chevalier-Boisvert, Lucas Willems, and Suman Pal · 2018
Cited alongside, same era.
Embodied question answering
Abhishek Das, Samyak Datta, Georgia Gkioxari, Stefan Lee, Devi Parikh, and Dhruv Batra · 2018
Cited alongside, same era.
Investigating human priors for playing video games
Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Thomas L. Griffiths, and Alexei A. Efros · 2018
Cited alongside, same era.
IMPALA: Scalable distributed deep-RL with importance weighted actor-learner architectures
Lasse Espeholt, Hubert Soyer, Remi Munos, Karen Simonyan, Vlad Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, and Koray Kavukcuoglu · 2018
Cited alongside, same era.
Unified pragmatic models for generating and following instructions
Daniel Fried, Jacob Andreas, and Dan Klein · 2018
Cited alongside, same era.
Representation learning for grounded spatial reasoning
Michael Janner, Karthik Narasimhan, and Regina Barzilay · 2018
Cited alongside, same era.
The NetHack learning environment
Heinrich Küttler, Nantas Nardelli, Alexander H Miller, Roberta Raileanu, Marco Selvatici, Edward Grefenstette, and Tim Rocktäschel · 2020
Later among the works it cites.
Harsh Mehta, Yoav Artzi, Jason Baldridge, Eugene Ie, and Piotr Mirowski · 2020
Later among the works it cites.
A benchmark for systematic generalization in grounded language understanding
Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt, and Brenden M. Lake · 2020
Later among the works it cites.
Movement pruning: Adaptive sparsity by fine-tuning
Victor Sanh, Thomas Wolf, and Alexander M. Rush · 2020
Later among the works it cites.
ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
Mohit Shridhar, Jesse Thomason, Daniel Gordon, Yonatan Bisk, Winson Han, Roozbeh Mottaghi, Luke Zettlemoyer, and Dieter Fox · 2020
Later among the works it cites.
dm_control: Software and tasks for continuous control
Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, and Nicolas Heess · 2020
Later among the works it cites.
Robots that use language
Stefanie Tellex, Nakul Gopalan, Hadas Kress-Gazit, and Cynthia Matuszek · 2020
Later among the works it cites.
Learning to stop: A simple yet effective approach to urban vision-language navigation
Jiannan Xiang, Xin Eric Wang, and William Yang Wang · 2020
Later among the works it cites.
RTFM: Generalising to Novel Environment Dynamics via Reading
Victor Zhong, Tim Rocktäschel, and Edward Grefenstette · 2020
Later among the works it cites.
Grounding language to entities and dynamics for generalization in reinforcement learning
Austin W. Hanjie, Victor Zhong, and Karthik Narasimhan · 2021
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Grounded language learning fast and slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, and Stephen Clark · 2021
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Minihack the planet: A sandbox for open-ended reinforcement learning research
Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Kuttler, Edward Grefenstette, and Tim Rocktäschel · 2021
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ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, and Matthew Hausknecht · 2021
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