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

Cite

Text

Lee et al. "What Is Right for Me Is Not yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning." International Joint Conference on Artificial Intelligence, 2022. doi:10.24963/IJCAI.2022/145

Markdown

[Lee et al. "What Is Right for Me Is Not yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning." International Joint Conference on Artificial Intelligence, 2022.](https://mlanthology.org/ijcai/2022/lee2022ijcai-right/) doi:10.24963/IJCAI.2022/145

BibTeX

@inproceedings{lee2022ijcai-right,
  title     = {{What Is Right for Me Is Not yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning}},
  author    = {Lee, Jae Hee and Kerzel, Matthias and Ahrens, Kyra and Weber, Cornelius and Wermter, Stefan},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {1039-1045},
  doi       = {10.24963/IJCAI.2022/145},
  url       = {https://mlanthology.org/ijcai/2022/lee2022ijcai-right/}
}