metadata
license: cc-by-4.0
task_categories:
- image-text-to-text
tags:
- safety
- multimodal
- implicit-risk
TriggerBench
TriggerBench is the first dataset explicitly modeling risk compositionality for multimodal implicit hazards. It contains 5,600 paired multimodal instances across 9 safety categories, with counterfactual contrastive pairs that decouple Key Elements and Trigger Elements to eliminate risk residues and encourage genuine logical deduction rather than superficial pattern matching.
The dataset is introduced in the paper ThinkingGuard: Decoding Implicit Hazards via Step-by-Step Risk Attribution in Multimodal Large Language Models. The official code and evaluation scripts are available in the GitHub repository.
Dataset details:
- 5,600 paired multimodal instances
- 3,864 train / 1,736 test
- 9 safety categories
- Counterfactual contrastive pairs separating Key Elements and Trigger Elements
Related model weights: ThinkingGuard-8B