Fetching the paper…
Reading the bibliography…
The ability to perform effective planning is crucial for building an instruction-following agent.
Learning to forget: Continual prediction with lstm
Felix A Gers, Jürgen Schmidhuber, and Fred Cummins · 1999
Earlier work this paper cites.
Incremental sampling-based algorithms for optimal motion planning
Sertac Karaman and Emilio Frazzoli · 2010
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel · 2015
Earlier work this paper cites.
Deep convolutional networks on graph-structured data
Mikael Henaff, Joan Bruna, and Yann LeCun · 2015
Earlier work this paper cites.
Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
Earlier work this paper cites.
Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer · 2015
Earlier work this paper cites.
Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
Earlier work this paper cites.
Structure inference machines: Recurrent neural networks for analyzing relations in group activity recognition
Zhiwei Deng, Arash Vahdat, Hexiang Hu, and Greg Mori · 2016
Earlier work this paper cites.
Professor forcing: A new algorithm for training recurrent networks
Alex M Lamb, Anirudh Goyal Alias Parth Goyal, Ying Zhang, Saizheng Zhang, Aaron C Courville, and Yoshua Bengio · 2016
Earlier work this paper cites.
Zero-shot task generalization with multi-task deep reinforcement learning
Junhyuk Oh, Satinder Singh, Honglak Lee, and Pushmeet Kohli · 2017
Earlier work this paper cites.
Neural map: Structured memory for deep reinforcement learning
Emilio Parisotto and Ruslan Salakhutdinov · 2017
Earlier work this paper cites.
Target-driven visual navigation in indoor scenes using deep reinforcement learning
Yuke Zhu, Roozbeh Mottaghi, Eric Kolve, Joseph J Lim, Abhinav Gupta, Li Fei-Fei, and Ali Farhadi · 2017
Earlier work this paper cites.
Cognitive mapping and planning for visual navigation
Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, and Jitendra Malik · 2017
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.
Graph-structured representations for visual question answering
Damien Teney, Lingqiao Liu, and Anton van Den Hengel · 2017
Earlier work this paper cites.
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Timothy Lillicrap · 2017
Earlier work this paper cites.
Unsupervised visual-linguistic reference resolution in instructional videos
De-An Huang, Joseph J Lim, Li Fei-Fei, and Juan Carlos Niebles · 2017
Cited alongside, same era.
Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 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.
Speaker-follower models for vision-and-language navigation
Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, and Trevor Darrell · 2018
Cited alongside, same era.
Learning to navigate in cities without a map
Piotr Mirowski, Matt Grimes, Mateusz Malinowski, Karl Moritz Hermann, Keith Anderson, Denis Teplyashin, Karen Simonyan, Andrew Zisserman, Raia Hadsell, et al · 2018
Chasing ghosts: Instruction following as bayesian state tracking
Peter Anderson, Ayush Shrivastava, Devi Parikh, Dhruv Batra, and Stefan Lee · 2019
Later among the works it cites.
Neural task graphs: Generalizing to unseen tasks from a single video demonstration
De-An Huang, Suraj Nair, Danfei Xu, Yuke Zhu, Animesh Garg, Li Fei-Fei, Silvio Savarese, and Juan Carlos Niebles · 2019
Later among the works it cites.
Neural graph evolution: Towards efficient automatic robot design
Tingwu Wang, Yuhao Zhou, Sanja Fidler, and Jimmy Ba · 2019
Later among the works it cites.
General evaluation for instruction conditioned navigation using dynamic time warping
Gabriel Ilharco, Vihan Jain, Alexander Ku, Eugene Ie, and Jason Baldridge · 2019
Later among the works it cites.
Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation
Xin Wang, Qiuyuan Huang, Asli Celikyilmaz, Jianfeng Gao, Dinghan Shen, Yuan-Fang Wang, William Yang Wang, and Lei Zhang · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Semi-parametric topological memory for navigation
Nikolay Savinov, Alexey Dosovitskiy, and Vladlen Koltun · 2018
Cited alongside, same era.
Nervenet: Learning structured policy with graph neural networks
Tingwu Wang, Renjie Liao, Jimmy Ba, and Sanja Fidler · 2018
Cited alongside, same era.
Neural graph matching networks for fewshot 3d action recognition
Michelle Guo, Edward Chou, De-An Huang, Shuran Song, Serena Yeung, and Li Fei-Fei · 2018
Cited alongside, same era.
Optimal completion distillation for sequence learning
Sara Sabour, William Chan, and Mohammad Norouzi · 2018
Cited alongside, same era.
Hierarchical graph representation learning with differentiable pooling
Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, Will Hamilton, and Jure Leskovec · 2018
Cited alongside, same era.
From language to goals: Inverse reinforcement learning for vision-based instruction following
Justin Fu, Anoop Korattikara, Sergey Levine, and Sergio Guadarrama · 2019
Cited alongside, same era.
Touchdown: Natural language navigation and spatial reasoning in visual street environments
Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely, and Yoav Artzi · 2019
Cited alongside, same era.
Later among the works it cites.
Vision-language navigation with self-supervised auxiliary reasoning tasks
Fengda Zhu, Yi Zhu, Xiaojun Chang, and Xiaodan Liang · 2019
Later among the works it cites.
Learning to navigate unseen environments: Back translation with environmental dropout
Hao Tan, Licheng Yu, and Mohit Bansal · 2019
Later among the works it cites.
Robust navigation with language pretraining and stochastic sampling
Xiujun Li, Chunyuan Li, Qiaolin Xia, Yonatan Bisk, Asli Celikyilmaz, Jianfeng Gao, Noah Smith, and Yejin Choi · 2019
Later among the works it cites.
Perceive, transform, and act: Multi-modal attention networks for vision-and-language navigation
Federico Landi, Lorenzo Baraldi, Marcella Cornia, Massimiliano Corsini, and Rita Cucchiara · 2019
Later among the works it cites.
Towards learning a generic agent for vision-and-language navigation via pre-training
Weituo Hao, Chunyuan Li, Xiujun Li, Lawrence Carin, and Jianfeng Gao · 2020
Closest in time.
Rmm: A recursive mental model for dialog navigation
Homero Roman Roman, Yonatan Bisk, Jesse Thomason, Asli Celikyilmaz, and Jianfeng Gao · 2020
Closest in time.
Learning to cooperate: Emergent communication in multi-agent navigation
Ivana Kajić, Eser Aygün, and Doina Precup · 2020
Closest in time.
Sparse graphical memory for robust planning
Michael Laskin, Scott Emmons, Ajay Jain, Thanard Kurutach, Pieter Abbeel, and Deepak Pathak · 2020
Closest in time.
Hallucinative topological memory for zero-shot visual planning
Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, and Aviv Tamar · 2020
Closest in time.
Interactive gibson benchmark: A benchmark for interactive navigation in cluttered environments
Fei Xia, William B Shen, Chengshu Li, Priya Kasimbeg, Micael Edmond Tchapmi, Alexander Toshev, Roberto Martín-Martín, and Silvio Savarese · 2020
Closest in time.
Spatio-temporal graph for video captioning with knowledge distillation
Boxiao Pan, Haoye Cai, De-An Huang, Kuan-Hui Lee, Adrien Gaidon, Ehsan Adeli, and Juan Carlos Niebles · 2020
Closest in time.
Improving vision-and-language navigation with image-text pairs from the web
Arjun Majumdar, Ayush Shrivastava, Stefan Lee, Peter Anderson, Devi Parikh, and Dhruv Batra · 2020
Closest in time.
Multi-view learning for vision-and-language navigation
Qiaolin Xia, Xiujun Li, Chunyuan Li, Yonatan Bisk, Zhifang Sui, Jianfeng Gao, Yejin Choi, and Noah A Smith · 2020
Closest in time.