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Language Model-Based Paired Variational Autoencoders for Robotic
  Language Learning

Language Model-Based Paired Variational Autoencoders for Robotic Language Learning

17 January 2022
Ozan Ozdemir
Matthias Kerzel
C. Weber
Jae Hee Lee
S. Wermter
    LM&Ro
ArXivPDFHTML

Papers citing "Language Model-Based Paired Variational Autoencoders for Robotic Language Learning"

4 / 4 papers shown
Title
Effect of Adaptive Communication Support on LLM-powered Human-Robot Collaboration
Effect of Adaptive Communication Support on LLM-powered Human-Robot Collaboration
Shipeng Liu
FNU Shrutika
Boshen Zhang
Zhehui Huang
Feifei Qian
Feifei Qian
64
0
0
26 Nov 2024
Details Make a Difference: Object State-Sensitive Neurorobotic Task
  Planning
Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning
Xiaowen Sun
Xufeng Zhao
Jae Hee Lee
Wenhao Lu
Matthias Kerzel
Stefan Wermter
LM&Ro
34
2
0
14 Jun 2024
EvoText: Enhancing Natural Language Generation Models via
  Self-Escalation Learning for Up-to-Date Knowledge and Improved Performance
EvoText: Enhancing Natural Language Generation Models via Self-Escalation Learning for Up-to-Date Knowledge and Improved Performance
Zheng Yuan
HU Xue
C. Zhang
Yongming Liu
VLM
12
0
0
08 Feb 2023
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,724
0
26 Sep 2016
1