Hateful Meme Classification On Pridemm
Metrics
Accuracy
F1
Results
Performance results of various models on this benchmark
| Paper Title | |||
|---|---|---|---|
| LMM-RGCL (Qwen2-VL-7B) | 78.1 | 78.4 | Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection |
| RGCL | 76.3 | 76.5 | Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning |
| MemeCLIP | 76.1 | 75.1 | MemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification |
| LMM-RGCL (Qwen2-VL-2B) | 76.0 | 76.7 | Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection |
| HateCLIPper | 75.5 | 74.1 | Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features |
| CLIP (fine-tuned) | 72.4 | 72.3 | Learning Transferable Visual Models From Natural Language Supervision |
0 of 6 row(s) selected.