DEMON24: ACM MM24 Demonstrative Instruction Following Challenge
We introduce the DEMON Challenge, defined as a benchmark for demonstrative instruction following, to ACM Multimedia 2024. The DEMON Challenge aims to assess the ability of models and systems to comprehend demonstrative instructions consisting of multiple, interleaved, and multimodal context that demonstrate the required information to complete a task. These instructions are curated from a diverse range of multi-modal datasets, spanning various fields and scenarios, to ensure comprehensive coverage and challenge diversity. The challenge details and participation information are available on the https://dcdmllm.github.io/DEMON-challenge/.
Authors
- Yueting Zhuang (ORCID: https://orcid.org/0000-0001-9017-2508)
- Juncheng Li (ORCID: https://orcid.org/0000-0003-2258-1291)
- Siliang Tang (ORCID: https://orcid.org/0000-0002-7356-9711)
- Zhiqi Ge
- Qifan Yu (ORCID: https://orcid.org/0000-0002-0190-5261)
- Wei Zhou (ORCID: https://orcid.org/0009-0003-4456-9741)
Institutions
- Zhejiang University (CN)
Publication Details
- Published
- 2024-10-26
- DOI
- https://doi.org/10.1145/3664647.3688993
- Citations
- 2
- Primary Topic
- Multimodal Machine Learning Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.50