Papers with causal interpretation of
V-SEAM: Visual Semantic Editing and Attention Modulating for Causal Interpretability of Vision-Language Models (2025.emnlp-main)
Copied to clipboard
| Challenge: | Existing work on causal interpretability focuses on large language models (LLMs) but internal mechanisms of vision-language models remain underexplored, authors say . |
| Approach: | They introduce a framework that combines visual and semantic manipulations for causal interpretation of vision-language models. |
| Outcome: | The proposed framework shows improved performance for LLAVA and InstructBLIP on three diverse benchmarks. |