CREDiT applies counterfactual reasoning via structural causal models to decompose video representations into causal and non-causal parts for more reliable VideoQA on datasets like NExT-GQA and SportsQA.
Attend what you need: Motion-appearance synergistic networks for video question answering,
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Counterfactual Reasoning for Fine-Grained Evidence Disentanglement in VideoQA
CREDiT applies counterfactual reasoning via structural causal models to decompose video representations into causal and non-causal parts for more reliable VideoQA on datasets like NExT-GQA and SportsQA.