Fetching the paper…
Reading the bibliography…
The search for a general model that can operate seamlessly across multiple domains remains a key goal in machine learning research.
Deconvolutional Networks
Zeiler, M. D., Krishnan, D., Taylor, G. W., and Fergus, R · 2010
Earlier work this paper cites.
MuJoCo: A physics engine for model-based control
Todorov, E., Erez, T., and Tassa, Y · 2012
Earlier work this paper cites.
The Arcade Learning Environment: An Evaluation Platform for General Agents
Bellemare, M. G., Naddaf, Y., Veness, J., and Bowling, M · 2013
Earlier work this paper cites.
Human-Level Control Through Deep Reinforcement Learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al · 2015
Earlier work this paper cites.
Zheng, Q., Zhang, A., and Grover, A · 2015
Earlier work this paper cites.
Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., and Zaremba, W · 2016
Earlier work this paper cites.
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
Parisotto, E., Ba, L. J., and Salakhutdinov, R · 2016
Earlier work this paper cites.
Rusu, A. A., Colmenarejo, S. G., Gülçehre, Ç., Desjardins, G., Kirkpatrick, J., Pascanu, R., Mnih, V., Kavukcuoglu, K., and Hadsell, R · 2016
Earlier work this paper cites.
Neural Machine Translation of Rare Words with Subword Units
Sennrich, R., Haddow, B., and Birch, A · 2016
Earlier work this paper cites.
Proximal Policy Optimization Algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O · 2017
Earlier work this paper cites.
Distral: Robust multitask reinforcement learning
Teh, Y. W., Bapst, V., Czarnecki, W. M., Quan, J., Kirkpatrick, J., Hadsell, R., Heess, N., and Pascanu, R · 2017
Earlier work this paper cites.
Attention is All you Need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I · 2017
Earlier work this paper cites.
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Espeholt, L., Soyer, H., Munos, R., Simonyan, K., Mnih, V., Ward, T., Doron, Y., Firoiu, V., Harley, T., Dunning, I., Legg, S., and Kavukcuoglu, K · 2018
Earlier work this paper cites.
Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning
Sharma, P., Ding, N., Goodman, S., and Soricut, R · 2018
Earlier work this paper cites.
Tassa, Y., Doron, Y., Muldal, A., Erez, T., Li, Y., de Las Casas, D., Budden, D., Abdolmaleki, A., Merel, J., Lefrancq, A., Lillicrap, T. P., and Riedmiller, M. A · 2018
Earlier work this paper cites.
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
Chevalier-Boisvert, M., Bahdanau, D., Lahlou, S., Willems, L., Saharia, C., Nguyen, T. H., and Bengio, Y · 2019
Earlier work this paper cites.
Recurrent Experience Replay in Distributed Reinforcement Learning
Kapturowski, S., Ostrovski, G., Quan, J., Munos, R., and Dabney, W · 2019
Earlier work this paper cites.
OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge
Marino, K., Rastegari, M., Farhadi, A., and Mottaghi, R · 2019
Cited alongside, same era.
Language Models are Unsupervised Multitask Learners
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I., et al · 2019
Cited alongside, same era.
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Yu, T., Quillen, D., He, Z., Julian, R., Hausman, K., Finn, C., and Levine, S · 2019
Cited alongside, same era.
Longformer: The Long-Document Transformer
Beltagy, I., Peters, M. E., and Cohan, A · 2020
Cited alongside, same era.
Language Models are Few-Shot Learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., and Amodei, D · 2020
Flamingo: a Visual Language Model for Few-Shot Learning
Alayrac, J., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., Ring, R., Rutherford, E., Cabi, S., Han, T., Gong, Z., Samangooei, S., Monteiro, M., Menick, J. L., Borgeaud, S., Brock, A., Nematzadeh, A., Sharifzadeh, S., Binkowski, M., Barreira, R., Vinyals, O., Zisserman, A., and Simonyan, K · 2022
Later among the works it cites.
Accelerate: Training and Inference at Scale Made Simple, Efficient and Adaptable
Gugger, S., Debut, L., Wolf, T., Schmid, P., Mueller, Z., Mangrulkar, S., Sun, M., and Bossan, B · 2022
Later among the works it cites.
VIMA: General Robot Manipulation with Multimodal Prompts
Jiang, Y., Gupta, A., Zhang, Z., Wang, G., Dou, Y., Chen, Y., Fei-Fei, L., Anandkumar, A., Zhu, Y., and Fan, L · 2022
Later among the works it cites.
Multi-Game Decision Transformers
Lee, K.-H., Nachum, O., Yang, M. S., Lee, L., Freeman, D., Guadarrama, S., Fischer, I., Xu, W., Jang, E., Michalewski, H., and Mordatch, I · 2022
Later among the works it cites.
Training Language Models to Follow Instructions with Human Feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C. L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Kelton, F., Miller, L., Simens, M., Askell, A., Welinder, P., Christiano, P. F., Leike, J., and Lowe, R · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
Ortiz Suárez, P. J., Romary, L., and Sagot, B · 2020
Cited alongside, same era.
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
Petrenko, A., Huang, Z., Kumar, T., Sukhatme, G. S., and Koltun, V · 2020
Cited alongside, same era.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., and Liu, P. J · 2020
Cited alongside, same era.
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
Song, H. F., Abdolmaleki, A., Springenberg, J. T., Clark, A., Soyer, H., Rae, J. W., Noury, S., Ahuja, A., Liu, S., Tirumala, D., Heess, N., Belov, D., Riedmiller, M. A., and Botvinick, M. M · 2020
Cited alongside, same era.
Transformers: State-of-the-Art Natural Language Processing
Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., Davison, J., Shleifer, S., von Platen, P., Ma, C., Jernite, Y., Plu, J., Xu, C., Scao, T. L., Gugger, S., Drame, M., Lhoest, Q., and Rush, A. M · 2020
Cited alongside, same era.
Multi-Task Reinforcement Learning with Soft Modularization
Yang, R., Xu, H., Wu, Y., and Wang, X · 2020
Cited alongside, same era.
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Agarwal, R., Schwarzer, M., Castro, P. S., Courville, A. C., and Bellemare, M. G · 2021
Cited alongside, same era.
Later among the works it cites.
A Generalist Agent
Reed, S., Zolna, K., Parisotto, E., Colmenarejo, S. G., Novikov, A., Barth-maron, G., Giménez, M., Sulsky, Y., Kay, J., Springenberg, J. T., Eccles, T., Bruce, J., Razavi, A., Edwards, A., Heess, N., Chen, Y., Hadsell, R., Vinyals, O., Bordbar, M., and de Freitas, N · 2022
Later among the works it cites.
A General Theoretical Paradigm to Understand Learning from Human Preferences
Azar, M. G., Rowland, M., Piot, B., Guo, D., Calandriello, D., Valko, M., and Munos, R · 2023
Later among the works it cites.
RT-1: Robotics Transformer for Real-World Control at Scale
Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Dabis, J., Finn, C., Gopalakrishnan, K., Hausman, K., Herzog, A., Hsu, J., Ibarz, J., Ichter, B., Irpan, A., Jackson, T., Jesmonth, S., Joshi, N. J., Julian, R., Kalashnikov, D., Kuang, Y., Leal, I., Lee, K., Levine, S., Lu, Y., Malla, U., Manjunath, D., Mordatch, I., Nachum, O., Parada, C., Peralta, J., Perez, E., Pertsch, K., Quiambao, J., Rao, K., Ryoo, M. S., Salazar, G., Sanketi, P. R., Sayed, K., Singh, J., Sontakke, S., Stone, A., Tan, C., Tran, H. T., Vanhoucke, V., Vega, S., Vuong, Q., Xia, F., Xiao, T., Xu, P., Xu, S., Yu, T., and Zitkovich, B · 2023
Later among the works it cites.
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
Chebotar, Y., Vuong, Q., Hausman, K., Xia, F., Lu, Y., Irpan, A., Kumar, A., Yu, T., Herzog, A., Pertsch, K., Gopalakrishnan, K., Ibarz, J., Nachum, O., Sontakke, S. A., Salazar, G., Tran, H. T., Peralta, J., Tan, C., Manjunath, D., Singh, J., Zitkovich, B., Jackson, T., Rao, K., Finn, C., and Levine, S · 2023
Later among the works it cites.
PaLI: A Jointly-Scaled Multilingual Language-Image Model
Chen, X., Wang, X., Changpinyo, S., Piergiovanni, A. J., Padlewski, P., Salz, D., Goodman, S., Grycner, A., Mustafa, B., Beyer, L., Kolesnikov, A., Puigcerver, J., Ding, N., Rong, K., Akbari, H., Mishra, G., Xue, L., Thapliyal, A. V., Bradbury, J., and Kuo, W · 2023
Later among the works it cites.
Chevalier-Boisvert, M., Dai, B., Towers, M., de Lazcano, R., Willems, L., Lahlou, S., Pal, S., Castro, P. S., and Terry, J · 2023
Later among the works it cites.
PaLM-E: An Embodied Multimodal Language Model
Driess, D., Xia, F., Sajjadi, M. S., Lynch, C., Chowdhery, A., Ichter, B., Wahid, A., Tompson, J., Vuong, Q., Yu, T., et al · 2023
Later among the works it cites.
A Survey on Transformers in Reinforcement Learning
Li, W., Luo, H., Lin, Z., Zhang, C., Lu, Z., and Ye, D · 2023
Later among the works it cites.
Emergent Agentic Transformer from Chain of Hindsight Experience
Liu, H. and Abbeel, P · 2023
Later among the works it cites.
HuggingFace’s Tokenizers, April 2023
Moi, A. and Patry, N · 2023
Later among the works it cites.
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Rafailov, R., Sharma, A., Mitchell, E., Manning, C. D., Ermon, S., and Finn, C · 2023
Later among the works it cites.