Summary of Solution For Emotion Prediction Competition Of Workshop on Emotionally and Culturally Intelligent Ai, by Shengdong Xu et al.
Solution for Emotion Prediction Competition of Workshop on Emotionally and Culturally Intelligent AI
by Shengdong Xu, Zhouyang Chi, Yang Yang
First submitted to arxiv on: 26 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed method, ECSP, aims to predict a person’s emotion through an artistic work with a comment in the WECIA Emotion Prediction Competition (EPC). The dataset, ArtELingo, addresses modal imbalance and language-cultural differences problems. To tackle this, a simple yet effective approach combines single-modal and multi-modal models using XLM-R-based unimodal and X²-VLM-based multimodal models, with an Emotion-Cultural specific prompt. This method ranked first in the final test with a score of 0.627. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper proposes a way to predict how someone feels based on art and comments. It uses a special kind of data called ArtELingo that helps with this task by balancing different types of information and taking into account cultural differences. The method combines single and multi-modal approaches using XLM-R and X²-VLM models, along with a prompt designed to reduce cultural differences. This approach did very well in a competition, achieving a score of 0.627. |
Keywords
» Artificial intelligence » Multi modal » Prompt
