Welcome to the Third Situated Interactive Multimodal Conversations (SIMMC 2.1) Track page for DSTC11 2022.

The SIMMC challenge aims to lay the foundations for the real-world assistant agents that can handle multimodal inputs, and perform multimodal actions. Specifically, we focus on the task-oriented dialogs that encompass a situated multimodal user context in the form of a co-observed & immersive virtual reality (VR) environment. The conversational context is dynamically updated on each turn based on the user actions (e.g. via verbal interactions, navigation within the scene).

The Second SIMMC challenge ended successfully, receiving a number of new state-of-the-art models in the novel multimodal dialog task. Building upon the success of the previous editions of the SIMMC challenges, we propose a third edition of the SIMMC challenge for the community to tackle and continue the effort towards building a successful multimodal assistant agent.

In this edition of the challenge, we specifically focus on the key challenge of fine-grained visual disambiguation, which adds an important skill to assistant agents studied in the previous SIMMC challenge. To accommodate for this challenge, we provide the improved version of the of the dataset, SIMMC 2.1, where we augment the SIMMC 2.0 dataset with additional annotations (i.e. identification of all possible referent candidates given ambiguous mentions) and corresponding re-paraphrases to support the study and modeling of visual disambiguation (SIMMC 2.1).

On Nov 4, 2022, the SIMMC challenge has successfully ended, receiving 15 model submissions across 5 teams from universities and industry. We thank everyone for their participation in the challenge. The detailed evaluation metrics and the links to the repositories can be found here.

Organizers: Seungwhan Moon, Satwik Kottur, Babak Damavandi, Alborz Geramifard

• [Nov 4, 2022] Results for DSTC11-SIMMC2.1 challenge entries have been announced.
• [Oct 21, 2022] Test-std dataset (SIMMC v2.1) is released. Start of Challenge Period 2.
• [June 28, 2022] DSTC11-SIMMC2.1 Challenge announcement. Training / development datasets (SIMMC v2.1) are released.

• SIMMC 2.1 Challenge Proposal (DSTC11)
• Task Description Paper (EMNLP 2021)
• Data Formats

NOTE: All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth"), unless otherwise noted.

For this edition of the challenge, we focus on four sub-tasks primarily aimed at replicating human-assistant actions in order to enable rich and interactive shopping scenarios.

For more detailed information on the new SIMMC 2.1 dataset and the instructions, please refer to the DSTC11 challenge proposal document.

Please check the task input file for a full description of inputs for each subtask.

We will provide the baselines for all the four tasks to benchmark their models. Feel free to use the code to bootstrap your model.

• Git clone our repository to download the datasets and the code. You may use the provided baselines as a starting point to develop your models.

$ git lfs install
$ git clone https://github.com/facebookresearch/simmc2.git

• Also please feel free to check out other open-sourced repositories from the previous SIMMC 2.0 challenge here.

• Submit your model prediction results on the devtest set, following the submission instructions.
• We will release the test-std set (with ground-truth labels hidden).

• Submit your model prediction results on the test-std set, following the submission instructions.
• We will evaluate the participants’ model predictions using the same evaluation script for Phase 1, and announce the results.

Please contact simmc@fb.com, or leave comments in the Github repository.

If you want to get the latest updates about DSTC10, join the DSTC mailing list.

If you want to publish experimental results with our datasets or use the baseline models, please cite the following articles:

@inproceedings{kottur-etal-2021-simmc,
    title = "{SIMMC} 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversations",
    author = "Kottur, Satwik  and
      Moon, Seungwhan  and
      Geramifard, Alborz  and
      Damavandi, Babak",
    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2021",
    address = "Online and Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.emnlp-main.401",
    doi = "10.18653/v1/2021.emnlp-main.401",
    pages = "4903--4912",
}

NOTE: The paper (EMNLP 2021) above describes in detail the datasets, the collection process, and some of the baselines we provide in this challenge.

SIMMC 2 is released under CC-BY-NC-SA-4.0, see LICENSE for details.