no code implementations • 13 Oct 2022 • Wangzhen Guo, Qinkang Gong, Hanjiang Lai
With the causal graph, a counterfactual inference is proposed to disentangle the disconnected reasoning from the total causal effect, which provides us a new perspective and technology to learn a QA model that exploits the true multi-hop reasoning instead of shortcuts.
no code implementations • 14 Jan 2022 • Qinkang Gong, Liangdao Wang, Hanjiang Lai, Yan Pan, Jian Yin
Specifically, from pixels to continuous features, we first propose a feature-preserving module, using the corrupted image as input to reconstruct the original feature from the pre-trained ViT model and the complete image, so that the feature extractor can focus on preserving the meaningful information of original data.