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What is Right for Me is Not Yet Right for You: A Dataset for Grounding
  Relative Directions via Multi-Task Learning

What is Right for Me is Not Yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning

5 May 2022
Jae Hee Lee
Matthias Kerzel
Kyra Ahrens
C. Weber
S. Wermter
ArXivPDFHTML

Papers citing "What is Right for Me is Not Yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning"

4 / 4 papers shown
Title
Visual Instruction Tuning with Polite Flamingo
Visual Instruction Tuning with Polite Flamingo
Delong Chen
Jianfeng Liu
Wenliang Dai
Baoyuan Wang
MLLM
34
42
0
03 Jul 2023
Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level
  Natural Language Explanations
Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations
Björn Plüster
Jakob Ambsdorf
Lukas Braach
Jae Hee Lee
S. Wermter
25
6
0
08 Dec 2022
Neuro-Symbolic Spatio-Temporal Reasoning
Neuro-Symbolic Spatio-Temporal Reasoning
Pascal Hitzler
Michael Sioutis
Md Kamruzzaman Sarker
Marjan Alirezaie
Aaron Eberhart
Stefan Wermter
NAI
28
0
0
28 Nov 2022
Knowing Earlier what Right Means to You: A Comprehensive VQA Dataset for
  Grounding Relative Directions via Multi-Task Learning
Knowing Earlier what Right Means to You: A Comprehensive VQA Dataset for Grounding Relative Directions via Multi-Task Learning
Kyra Ahrens
Matthias Kerzel
Jae Hee Lee
C. Weber
S. Wermter
14
0
0
06 Jul 2022
1