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In learning an embodied agent executing daily tasks via language directives, the literature largely assumes that the agent learns all training data at the beginning.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Roger Ratcliff · 1990
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell · 2017
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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
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Mapping instructions and visual observations to actions with reinforcement learning
Dipendra Misra, John Langford, and Yoav Artzi · 2017
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Visual semantic planning using deep successor representations
Yuke Zhu, Daniel Gordon, Eric Kolve, Dieter Fox, Li Fei-Fei, Abhinav Gupta, Roozbeh Mottaghi, and Ali Farhadi · 2017
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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
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K Dokania, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
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Embodied question answering
Abhishek Das, Samyak Datta, Georgia Gkioxari, Stefan Lee, Devi Parikh, and Dhruv Batra · 2018
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Iqa: Visual question answering in interactive environments
Daniel Gordon, Aniruddha Kembhavi, Mohammad Rastegari, Joseph Redmon, Dieter Fox, and Ali Farhadi · 2018
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Environments for lifelong reinforcement learning
Khimya Khetarpal, Shagun Sodhani, Sarath Chandar, and Doina Precup · 2018
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Lifelong inverse reinforcement learning
Jorge Mendez, Shashank Shivkumar, and Eric Eaton · 2018
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Autoaugment: Learning augmentation policies from data
Ekin Dogus Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V. Le · 2019
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Stay on the path: Instruction fidelity in vision-and-language navigation
Vihan Jain, Gabriel Magalhaes, Alexander Ku, Ashish Vaswani, Eugene Ie, and Jason Baldridge · 2019
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Regularization shortcomings for continual learning
Timothée Lesort, Andrei Stoian, and David Filliat · 2019
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An exponential learning rate schedule for deep learning
Zhiyuan Li and Sanjeev Arora · 2019
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Self-monitoring navigation agent via auxiliary progress estimation
Chih-Yao Ma, Jiasen Lu, Zuxuan Wu, Ghassan AlRegib, Zsolt Kira, Richard Socher, and Caiming Xiong · 2019
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
Earlier work this paper cites.
Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne · 2019
Earlier work this paper cites.
Habitat: A Platform for Embodied AI Research
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, Devi Parikh, and Dhruv Batra · 2019
Earlier work this paper cites.
Large scale incremental learning
Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, and Yun Fu · 2019
Cited alongside, same era.
Continual lifelong learning in natural language processing: A survey
Magdalena Biesialska, Katarzyna Biesialska, and Marta R Costa-Jussa · 2020
Cited alongside, same era.
Dark experience for general continual learning: a strong, simple baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and Simone Calderara · 2020
Cited alongside, same era.
Superensemble classifier for improving predictions in imbalanced datasets
Tanujit Chakraborty and Ashis Kumar Chakraborty · 2020
Cited alongside, same era.
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
Cited alongside, same era.
Modeling missing annotations for incremental learning in object detection
Fabio Cermelli, Antonino Geraci, Dario Fontanel, and Barbara Caputo · 2022
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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
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Dialfred: Dialogue-enabled agents for embodied instruction following
Xiaofeng Gao, Qiaozi Gao, Ran Gong, Kaixiang Lin, Govind Thattai, and Gaurav S Sukhatme · 2022
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Online continual learning for embedded devices
Tyler L Hayes and Christopher Kanan · 2022
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Rethinking task-incremental learning baselines
Md Sazzad Hossain, Pritom Saha, Townim Faisal Chowdhury, Shafin Rahman, Fuad Rahman, and Nabeel Mohammed · 2022
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Matt Deitke, Winson Han, Alvaro Herrasti, Aniruddha Kembhavi, Eric Kolve, Roozbeh Mottaghi, Jordi Salvador, Dustin Schwenk, Eli VanderBilt, Matthew Wallingford, Luca Weihs, Mark Yatskar, and Ali Farhadi · 2020
Cited alongside, same era.
Beyond the nav-graph: Vision-and-language navigation in continuous environments
Jacob Krantz, Erik Wijmans, Arjun Majumdar, Dhruv Batra, and Stefan Lee · 2020
Cited alongside, same era.
Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, and Natalia Díaz-Rodríguez · 2020
Cited alongside, same era.
Gdumb: A simple approach that questions our progress in continual learning
Ameya Prabhu, Philip HS Torr, and Puneet K Dokania · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Rainbow memory: Continual learning with a memory of diverse samples
Jihwan Bang, Heesu Kim, YoungJoon Yoo, Jung-Woo Ha, and Jonghyun Choi · 2021
Cited alongside, same era.
Manipulathor: A framework for visual object manipulation
Kiana Ehsani, Winson Han, Alvaro Herrasti, Eli VanderBilt, Luca Weihs, Eric Kolve, Aniruddha Kembhavi, and Roozbeh Mottaghi · 2021
Cited alongside, same era.
Online continual learning on class incremental blurry task configuration with anytime inference
Hyunseo Koh, Dahyun Kim, Jung-Woo Ha, and Jonghyun Choi · 2022
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Carm: hierarchical episodic memory for continual learning
Soobee Lee, Minindu Weerakoon, Jonghyun Choi, Minjia Zhang, Di Wang, and Myeongjae Jeon · 2022
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Long-tailed class incremental learning
Xialei Liu, Yu-Song Hu, Xu-Sheng Cao, Andrew D Bagdanov, Ke Li, and Ming-Ming Cheng · 2022
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Online continual learning in image classification: An empirical survey
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, and Scott Sanner · 2022
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Film: Following instructions in language with modular methods
So Yeon Min, Devendra Singh Chaplot, Pradeep Ravikumar, Yonatan Bisk, and Ruslan Salakhutdinov · 2022
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Teach: Task-driven embodied agents that chat
Aishwarya Padmakumar, Jesse Thomason, Ayush Shrivastava, Patrick Lange, Anjali Narayan-Chen, Spandana Gella, Robinson Piramuthu, Gokhan Tur, and Dilek Hakkani-Tur · 2022
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Cora: Benchmarks, baselines, and metrics as a platform for continual reinforcement learning agents
Sam Powers, Eliot Xing, Eric Kolve, Roozbeh Mottaghi, and Abhinav Gupta · 2022
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vclimb: A novel video class incremental learning benchmark
Andrés Villa, Kumail Alhamoud, Victor Escorcia, Fabian Caba, Juan León Alcázar, and Bernard Ghanem · 2022
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Learning to prompt for continual learning
Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, and Tomas Pfister · 2022
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Lifelong robotic reinforcement learning by retaining experiences
Annie Xie and Chelsea Finn · 2022
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Evaluations of the gap between supervised and reinforcement lifelong learning on robotic manipulation tasks
Fan Yang, Chao Yang, Huaping Liu, and Fuchun Sun · 2022
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Task-free continual learning via online discrepancy distance learning
Fei Ye and Adrian G Bors · 2022
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Multi-level compositional reasoning for interactive instruction following
Suvvansh Bhambri, Byeonghwi Kim, and Jonghyun Choi · 2023
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Long-tailed continual learning for visual food recognition
Jiangpeng He, Luotao Lin, Jack Ma, Heather A Eicher-Miller, and Fengqing Zhu · 2023
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Context-aware planning and environment-aware memory for instruction following embodied agents
Byeonghwi Kim, Jinyeon Kim, Yuyeong Kim, Cheolhong Min, and Jonghyun Choi · 2023
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Online boundary-free continual learning by scheduled data prior
Hyunseo Koh, Minhyuk Seo, Jihwan Bang, Hwanjun Song, Deokki Hong, Seulki Park, Jung-Woo Ha, and Jonghyun Choi · 2023
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Libero: Benchmarking knowledge transfer for lifelong robot learning
Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, and Peter Stone · 2023
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Computationally budgeted continual learning: What does matter?
Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet K Dokania, Philip HS Torr, Ser-Nam Lim, Bernard Ghanem, and Adel Bibi · 2023
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Voyager: An open-ended embodied agent with large language models
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, and Anima Anandkumar · 2023
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