Scope
This direction focuses on robust multimodal reasoning where social, cultural, and contextual priors matter.
Current Questions
- How can models distinguish factual evidence from cultural assumptions?
- Which evaluation setup best captures context-aware failure modes?
- How should multilingual and multimodal signals be fused?
Milestones
- Expand culturally diverse evaluation sets.
- Build error taxonomies for context-sensitive failures.
- Propose training recipes and release benchmark reports.