@misc{myers2025temporal,
    author       = {Myers, Vivek and Zheng, Bill Chunyuan and Dragan, Anca and Fang, Kuan
                    and Levine, Sergey},
    eprint       = {2502.05454},
    eprinttype   = {arXiv},
    howpublished = {arXiv:2502.05454},
    title        = {{Temporal Representation Alignment}: {Successor Features Enable
                    Emergent Compositionality} in {Robot Instruction Following}},
    url          = {https://arxiv.org/abs/2502.05454},
    year         = {2025},
}

@inproceedings{myers2025horizon,
    author    = {Myers, Vivek and Ji, Catherine and Eysenbach, Benjamin},
    booktitle = {{International Conference} on {Learning Representations}},
    month     = jan,
    title     = {{Horizon Generalization} in {Reinforcement Learning}},
    url       = {https://arxiv.org/pdf/2501.02709},
    year      = {2025},
}

@inproceedings{bortkiewicz2025accelerating,
    author    = {Bortkiewicz, Micha\l{} and Pa\l{}ucki, W\l{}adek and Myers, Vivek and
                 Dziarmaga, Tadeusz and Arczewski, Tomasz and Kuci\'{n}ski, \L{}ukasz and
                 Eysenbach, Benjamin},
    booktitle = {{International Conference} on {Learning Representations}},
    title     = {{Accelerating Goal-Conditioned RL Algorithms} and {Research}},
    url       = {https://arxiv.org/pdf/2408.11052},
    year      = {2025},
}

@inproceedings{myers2024learninga,
    author    = {Myers, Vivek and Ellis, Evan and Levine, Sergey and Eysenbach, Benjamin
                 and Dragan, Anca},
    booktitle = {{Neural Information Processing Systems}},
    month     = dec,
    title     = {{Learning} to {Assist Humans Without Inferring Rewards}},
    url       = {https://arxiv.org/pdf/2411.02623},
    year      = {2024},
}

@inproceedings{eysenbach2024inference,
    author    = {Eysenbach, Benjamin and Myers, Vivek and Salakhutdinov, Ruslan and Levine,
                 Sergey},
    booktitle = {{Neural Information Processing Systems}},
    month     = dec,
    title     = {{Inference} via {Interpolation}: {Contrastive Representations Provably
                 Enable Planning} and {Inference}},
    url       = {https://arxiv.org/pdf/2403.04082},
    year      = {2024},
}

@inproceedings{myers2024policy,
    author    = {Myers, Vivek and Zheng, Bill Chunyuan and Mees, Oier and Levine, Sergey
                 and Fang, Kuan},
    booktitle = {{Conference} on {Robot Learning}},
    month     = nov,
    title     = {{Policy Adaptation} via {Language Optimization}: {Decomposing Tasks} for
                 {Few-Shot Imitation}},
    url       = {https://arxiv.org/pdf/2408.16228},
    year      = {2024},
}

@inproceedings{myers2024learning,
    author    = {Myers, Vivek and Zheng, Chongyi and Dragan, Anca and Levine, Sergey and
                 Eysenbach, Benjamin},
    booktitle = {{International Conference} on {Machine Learning}},
    title     = {{Learning Temporal Distances}: {Contrastive Successor Features Can
                 Provide} a {Metric Structure} for {Decision-Making}},
    url       = {https://proceedings.mlr.press/v235/myers24a.html},
    year      = {2024},
}

@inproceedings{pan2024coprocessor,
    author    = {Pan, Michelle and Schrum, Mariah and Myers, Vivek and B\i{}y\i{}k, Erdem
                 and Dragan, Anca},
    booktitle = {{International Conference} on {Machine Learning}},
    title     = {{Coprocessor Actor Critic}: A {Model-Based Reinforcement Learning
                 Approach} for {Adaptive Brain Stimulation}},
    url       = {https://arxiv.org/pdf/2406.06714},
    year      = {2024},
}

@inproceedings{kwon2023grounded,
    author    = {Kwon, Minae and Hu, Hengyuan and Myers, Vivek and Karamcheti, Siddharth
                 and Dragan, Anca and Sadigh, Dorsa},
    booktitle = {{IEEE International Conference} on {Robotics} and {Automation}},
    title     = {{Toward Grounded Commonsense Reasoning}},
    url       = {https://arxiv.org/pdf/2306.08651},
    year      = {2024},
}

@inproceedings{walke2023bridgedata,
    author    = {Walke, Homer and Black, Kevin and Lee, Abraham and Kim, Moo Jin and Du,
                 Max and Zheng, Chongyi and Zhao, Tony and Estruch, Philippe Hansen- and
                 Vuong, Quan and He, Andre and Myers, Vivek and Fang, Kuan and Finn,
                 Chelsea and Levine, Sergey},
    booktitle = {{Conference} on {Robot Learning}},
    title     = {{BridgeData} {V2}: A {Dataset} for {Robot Learning} at {Scale}},
    url       = {https://arxiv.org/pdf/2308.12952},
    year      = {2023},
}

@inproceedings{myers2023goal,
    author    = {Myers, Vivek and He, Andre and Fang, Kuan and Walke, Homer and Estruch,
                 Phillipe Hansen- and Cheng, Ching-An and Jalobeanu, Mihai and Kolobov,
                 Andrey and Dragan, Anca and Levine, Sergey},
    booktitle = {{Conference} on {Robot Learning}},
    title     = {{Goal Representations} for {Instruction Following}: A {Semi-Supervised
                 Language Interface} to {Control}},
    url       = {https://proceedings.mlr.press/v229/myers23a.html},
    year      = {2023},
}

@inproceedings{myers2023active,
    author    = {Myers, Vivek and B\i{}y\i{}k, Erdem and Sadigh, Dorsa},
    booktitle = {{IEEE International Conference} on {Robotics} and {Automation}},
    title     = {{Active Reward Learning From Online Preferences}},
    url       = {https://arxiv.org/pdf/2302.13507},
    year      = {2023},
}

@inproceedings{myers2021learning,
    author    = {Myers, Vivek and B\i{}y\i{}k, Erdem and Anari, Nima and Sadigh, Dorsa},
    booktitle = {{Conference} on {Robot Learning}},
    title     = {{Learning Multimodal Rewards From Rankings}},
    url       = {https://iliad.stanford.edu/pdfs/publications/myers2021learning.pdf},
    year      = {2021},
}

@article{gruver2021effective,
    author  = {Gruver, Nate and Stanton, Samuel and Kirichenko, Polina and Finzi, Marc and
               Maffettone, Phillip and Myers, Vivek and Delaney, Emily and Greenside,
               Peyton and Wilson, Andrew Gordon},
    journal = {{ICML} 2021 {Workshop} on {Computational Biology}},
    title   = {{Effective Surrogate Models} for {Protein Design With Bayesian
               Optimization}},
    url     = {https://icml-compbio.github.io/icml-website-2021/2021/papers/WCBICML2021_paper_61.pdf},
    year    = {2021},
}

@article{myers2020hierarchical,
    author  = {Myers, Vivek and Greenside, Peyton},
    journal = {{ICML} 2020 {Workshop} on {Real World Experiment Design} and {Active
               Learning}},
    title   = {A {Hierarchical Approach} to {Scaling Batch Active Search Over Structured
               Data}},
    url     = {https://arxiv.org/pdf/2007.10263},
    year    = {2020},
}