Fetching the paper…
Reading the bibliography…
High sample complexity has long been a challenge for RL.
Policy gradient methods for reinforcement learning with function approximation
Richard S Sutton, David McAllester, Satinder Singh, and Yishay Mansour · 1999
Earlier work this paper cites.
Reading to learn: Constructing features from semantic abstracts
Jacob Eisenstein, James Clarke, Dan Goldwasser, and Dan Roth · 2009
Earlier work this paper cites.
Alfworld: Aligning text and embodied environments for interactive learning
Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, and Matthew Hausknecht · 2010
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.
Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
Earlier work this paper cites.
Simple online and realtime tracking
Alex Bewley, Zongyuan Ge, Lionel Ott, Fabio Ramos, and Ben Upcroft · 2016
Earlier work this paper cites.
Listen, attend, and walk: Neural mapping of navigational instructions to action sequences
Hongyuan Mei, Mohit Bansal, and Matthew R Walter · 2016
Earlier work this paper cites.
Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
Earlier work this paper cites.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
Earlier work this paper cites.
Learning language games through interaction
Sida I Wang, Percy Liang, and Christopher D Manning · 2016
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.
AI2-THOR: An Interactive 3D Environment for Visual AI
Eric Kolve, Roozbeh Mottaghi, Winson Han, Eli VanderBilt, Luca Weihs, Alvaro Herrasti, Daniel Gordon, Yuke Zhu, Abhinav Gupta, and Ali Farhadi · 2017
Earlier work this paper cites.
Mapping instructions and visual observations to actions with reinforcement learning
Dipendra Misra, John Langford, and Yoav Artzi · 2017
Earlier work this paper cites.
Curiosity-driven exploration by self-supervised prediction
Deepak Pathak, Pulkit Agrawal, Alexei A Efros, and Trevor Darrell · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Earlier work this paper cites.
Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
Earlier work this paper cites.
Learning to understand goal specifications by modelling reward
Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Arian Hosseini, Pushmeet Kohli, and Edward Grefenstette · 2018
Earlier work this paper cites.
Gated-attention architectures for task-oriented language grounding
Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, and Ruslan Salakhutdinov · 2018
Earlier work this paper cites.
Babyai: A platform to study the sample efficiency of grounded language learning
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, and Yoshua Bengio · 2018
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Addressing function approximation error in actor-critic methods
Scott Fujimoto, Herke Hoof, and David Meger · 2018
Earlier work this paper cites.
Soft actor-critic algorithms and applications
Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, et al · 2018
Cited alongside, same era.
Representation learning for grounded spatial reasoning
Michael Janner, Karthik Narasimhan, and Regina Barzilay · 2018
Cited alongside, same era.
Recurrent experience replay in distributed reinforcement learning
Steven Kapturowski, Georg Ostrovski, John Quan, Remi Munos, and Will Dabney · 2018
Cited alongside, same era.
Grounding language for transfer in deep reinforcement learning
Karthik Narasimhan, Regina Barzilay, and Tommi Jaakkola · 2018
Cited alongside, same era.
Unsupervised state representation learning in atari
Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, and R Devon Hjelm · 2019
Cited alongside, same era.
Film: Following instructions in language with modular methods
So Yeon Min, Devendra Singh Chaplot, Pradeep Ravikumar, Yonatan Bisk, and Ruslan Salakhutdinov · 2021
Later among the works it cites.
Episodic transformer for vision-and-language navigation
Alexander Pashevich, Cordelia Schmid, and Chen Sun · 2021
Later among the works it cites.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Later among the works it cites.
Reward is enough
David Silver, Satinder Singh, Doina Precup, and Richard S. Sutton · 2021
Later among the works it cites.
Habitat 2.0: Training home assistants to rearrange their habitat
Andrew Szot, Alexander Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John Turner, Noah Maestre, Mustafa Mukadam, Devendra Singh Chaplot, Oleksandr Maksymets, et al · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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.
Using natural language for reward shaping in reinforcement learning
Prasoon Goyal, Scott Niekum, and Raymond J Mooney · 2019
Cited alongside, same era.
Stabilizing off-policy q-learning via bootstrapping error reduction
Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, and Sergey Levine · 2019
Cited alongside, same era.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
Cited alongside, same era.
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
Cited alongside, same era.
rlpyt: A research code base for deep reinforcement learning in pytorch
Adam Stooke and Pieter Abbeel · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Later among the works it cites.
General-purpose question-answering with macaw
Oyvind Tafjord and Peter Clark · 2021
Later among the works it cites.
Learning to solve complex tasks by growing knowledge culturally across generations
Michael Henry Tessler, Jason Madeano, Pedro A Tsividis, Brin Harper, Noah D Goodman, and Joshua B Tenenbaum · 2021
Later among the works it cites.
Grounding language to entities and dynamics for generalization in reinforcement learning
HJ Wang and Karthik Narasimhan · 2021
Later among the works it cites.
Readtwice: Reading very large documents with memories
Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong, Philip Pham, Ilya Eckstein, and Fei Sha · 2021
Later among the works it cites.
Silg: The multi-environment symbolic interactive language grounding benchmark
Victor Zhong, Austin W Hanjie, Sida I Wang, Karthik Narasimhan, and Luke Zettlemoyer · 2021
Later among the works it cites.
Do as i can, not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, et al · 2022
Later among the works it cites.
Generalized data distribution iteration
Jiajun Fan and Changnan Xiao · 2022
Later among the works it cites.
Minedojo: Building open-ended embodied agents with internet-scale knowledge
Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, and Anima Anandkumar · 2022
Later among the works it cites.
Deep RL Zoo: A collections of deep rl algorithms implemented with pytorch, 2022
Michael Hu · 2022
Later among the works it cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
Later among the works it cites.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Later among the works it cites.
Learning interactive driving policies via data-driven simulation
Tsun-Hsuan Wang, Alexander Amini, Wilko Schwarting, Igor Gilitschenski, Sertac Karaman, and Daniela Rus · 2022
Later among the works it cites.
Segment everything everywhere all at once
Xueyan Zou, Jianwei Yang, Hao Zhang, Feng Li, Linjie Li, Jianfeng Gao, and Yong Jae Lee · 2022
Later among the works it cites.
Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
Closest in time.
Palm-e: An embodied multimodal language model
Danny Driess, Fei Xia, Mehdi SM Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, et al · 2023
Closest in time.
Grounding dino: Marrying dino with grounded pre-training for open-set object detection
Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, et al · 2023
Closest in time.
Plan, eliminate, and track–language models are good teachers for embodied agents
Yue Wu, So Yeon Min, Yonatan Bisk, Ruslan Salakhutdinov, Amos Azaria, Yuanzhi Li, Tom Mitchell, and Shrimai Prabhumoye · 2023
Closest in time.