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Imagining In-distribution States: How Predictable Robot Behavior Can
  Enable User Control Over Learned Policies

Imagining In-distribution States: How Predictable Robot Behavior Can Enable User Control Over Learned Policies

19 June 2024
Isaac S. Sheidlower
Emma Bethel
Douglas Lilly
Reuben M. Aronson
E. Short
ArXivPDFHTML

Papers citing "Imagining In-distribution States: How Predictable Robot Behavior Can Enable User Control Over Learned Policies"

4 / 4 papers shown
Title
Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulation
Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulation
Mohit Shridhar
Lucas Manuelli
D. Fox
LM&Ro
163
457
0
12 Sep 2022
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming
Rohan R. Paleja
Muyleng Ghuy
Nadun R. Arachchige
Reed Jensen
Matthew C. Gombolay
78
63
0
08 Sep 2022
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
185
879
0
21 Oct 2021
Lifelong Robotic Reinforcement Learning by Retaining Experiences
Lifelong Robotic Reinforcement Learning by Retaining Experiences
Annie Xie
Chelsea Finn
OffRL
CLL
106
43
0
19 Sep 2021
1