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2009.14108
Cited By
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
29 September 2020
Vihang Patil
M. Hofmarcher
Marius-Constantin Dinu
Matthias Dorfer
P. Blies
Johannes Brandstetter
Jose A. Arjona-Medina
Sepp Hochreiter
Re-assign community
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Papers citing
"Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution"
6 / 6 papers shown
Title
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
Thomas Schmied
Thomas Adler
Vihang Patil
M. Beck
Korbinian Poppel
Johannes Brandstetter
G. Klambauer
Razvan Pascanu
Sepp Hochreiter
73
4
0
21 Feb 2025
Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents
Zihao Wang
Shaofei Cai
Guanzhou Chen
Anji Liu
Xiaojian Ma
Yitao Liang
LM&Ro
LLMAG
55
315
0
03 Feb 2023
Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling
Kolby Nottingham
Prithviraj Ammanabrolu
Alane Suhr
Yejin Choi
Hannaneh Hajishirzi
Sameer Singh
Roy Fox
LLMAG
LM&Ro
28
76
0
28 Jan 2023
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning
C. Steinparz
Thomas Schmied
Fabian Paischer
Marius-Constantin Dinu
Vihang Patil
Angela Bitto-Nemling
Hamid Eghbalzadeh
Sepp Hochreiter
CLL
8
11
0
12 Jul 2022
A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning
Youssef Diouane
Aurélien Lucchi
Vihang Patil
16
3
0
21 Feb 2022
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP
Andreas Fürst
Elisabeth Rumetshofer
Johannes Lehner
Viet-Hung Tran
Fei Tang
...
David P. Kreil
Michael K Kopp
G. Klambauer
Angela Bitto-Nemling
Sepp Hochreiter
VLM
CLIP
199
102
0
21 Oct 2021
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