EAM2021: 2nd Workshop on Emerging Advances in Multimodal AI (EAM) Taiwan/Remote Taipei, Taiwan, November 15-17, 2021 |
Conference website | https://sharechat.com/events/abuse-detection-challenge |
Submission link | https://easychair.org/conferences/?conf=eam2021 |
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
Research Paper Track
The research paper track welcomes papers on all topics related to multi-modal AI with interesting real-world use cases and good practical pipelines and frameworks. We recognize that high-quality research on rich application domains often leads to papers along multiple dimensions. These are motivated by the following issues:
- Data collection may be difficult and may require innovative methods and validations, for instance, to address large scale data gathering in the field, eliminate bias and ensure fairness.
- Problem modeling is a time-intensive activity that requires significant collaborations with domain experts and needs to balance a variety of tradeoffs in decision making.
- Real-world impact may be realized through time-consuming field studies that typically compare a baseline with the application of novel algorithms in the real world, and the experimental design can be challenging and the evaluation may be multifaceted.
Moj Multilingual Abusive Comment Identification - Challenge
An innovative new challenge towards combating abusive comments on Moj, one of India's largest short-video apps in multiple regional languages. We invite submissions to a grand challenge, where the goal is to develop AI solutions for predicting abusive comments posted on the Moj app in 15+ languages given natural language data along with contextual user data. Key novelties around this dataset include:
- Massive & Multilungual - 15+ low-resource Indic languages
- Gold standard human annotated
- User profiling information such as commentor's last 10 posts, timestamps, etc. for author profiling
- Metadata based explicit feedback like #likes, #reports on each comment
Top performing teams (based on Kaggle leaderboard) will be eligible for prizes sponsored by ShareChat, and will also be considered for internship/full-time positions at IIIT-Delhi and/or ShareChat.
Committees
All details here: https://sharechat.com/events/abuse-detection-challenge
Contact
All questions about submissions should be emailed to ramitsawhney@sharechat.co, eam2021@sharechat.co