 Our proposed cause-effect look 1) is general to any baseline VQA architecture , 2) achieves significant improvement on the language-bias sensitive VQA-CP dataset , and 3) fills the theoretical gap in recent language prior based works .
<clarity>  Our proposed cause-effect look 1) is general to any baseline VQA architecture , 2) achieves significant improvement on the language-bias sensitive VQA-CP dataset , and 3) fills the theoretical gap in recent language prior based works .
 Our proposed cause-effect look 1) is general to any baseline VQA architecture , 2) achieves competitive performance on the language-bias sensitive VQA-CP dataset , and 3) fills the theoretical gap in recent language prior based works .