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While vision-language-action models (VLAs) have shown promising robotic behaviors across a diverse set of manipulation tasks, they achieve limited success rates when deployed on novel tasks out of the box.
Hierarchical grouping to optimize an objective function
Joe H Ward Jr · 1963
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Algorithmic learning in a random world , volume 29
Vladimir Vovk, Alexander Gammerman, and Glenn Shafer · 2005
Earlier work this paper cites.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
Earlier work this paper cites.
On the analysis of movement smoothness
Sivakumar Balasubramanian, Alejandro Melendez-Calderon, Agnes Roby-Brami, and Etienne Burdet · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 2018
Earlier work this paper cites.
Trevor Ablett, Filip Marić, and Jonathan Kelly · 2020
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Andrey Malinin and Mark J. F. Gales · 2021
Earlier work this paper cites.
A gentle introduction to conformal prediction and distribution-free uncertainty quantification
Anastasios N Angelopoulos and Stephen Bates · 2021
Earlier work this paper cites.
Out-of-distribution detection for automotive perception
Julia Nitsch, Masha Itkina, Ransalu Senanayake, Juan Nieto, Max Schmidt, Roland Siegwart, Mykel J Kochenderfer, and Cesar Cadena · 2021
Earlier work this paper cites.
Adaptive conformal inference under distribution shift
Isaac Gibbs and Emmanuel Candes · 2021
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Failure prediction with statistical guarantees for vision-based robot control
Alec Farid, David Snyder, Allen Z. Ren, and Anirudha Majumdar · 2022
Earlier work this paper cites.
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Rohan Sinha, Apoorva Sharma, Somrita Banerjee, Thomas Lew, Rachel Luo, Spencer M Richards, Yixiao Sun, Edward Schmerling, and Marco Pavone · 2022
Earlier work this paper cites.
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Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, et al · 2023
Earlier work this paper cites.
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Earlier work this paper cites.
Closing the loop on runtime monitors with fallback-safe mpc
Rohan Sinha, Edward Schmerling, and Marco Pavone · 2023
Earlier work this paper cites.
Vision-language models as success detectors
Yuqing Du, Ksenia Konyushkova, Misha Denil, Akhil Raju, Jessica Landon, Felix Hill, Nando de Freitas, and Serkan Cabi · 2023
Earlier work this paper cites.
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Cited alongside, same era.
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ReDiffuser: Reliable decision-making using a diffuser with confidence estimation
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