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pro vyhledávání: '"Zhang, Jindi"'
Machine learning systems produce biased results towards certain demographic groups, known as the fairness problem. Recent approaches to tackle this problem learn a latent code (i.e., representation) through disentangled representation learning and th
Externí odkaz:
http://arxiv.org/abs/2305.12178
We examined whether embedding human attention knowledge into saliency-based explainable AI (XAI) methods for computer vision models could enhance their plausibility and faithfulness. We first developed new gradient-based XAI methods for object detect
Externí odkaz:
http://arxiv.org/abs/2305.03601
Autor:
Zhang, Jindi
Autonomous driving technology has drawn a lot of attention due to its fast development and extremely high commercial values. The recent technological leap of autonomous driving can be primarily attributed to the progress in the environment perception
Externí odkaz:
http://arxiv.org/abs/2203.16130
Long-form question answering (LFQA) aims to generate a paragraph-length answer for a given question. While current work on LFQA using large pre-trained model for generation are effective at producing fluent and somewhat relevant content, one primary
Externí odkaz:
http://arxiv.org/abs/2203.00343
Publikováno v:
In Neural Networks September 2024 177
For autonomous driving, an essential task is to detect surrounding objects accurately. To this end, most existing systems use optical devices, including cameras and light detection and ranging (LiDAR) sensors, to collect environment data in real time
Externí odkaz:
http://arxiv.org/abs/2110.10523
In recent years, many deep learning models have been adopted in autonomous driving. At the same time, these models introduce new vulnerabilities that may compromise the safety of autonomous vehicles. Specifically, recent studies have demonstrated tha
Externí odkaz:
http://arxiv.org/abs/2108.02940
Autor:
Zhang, Lili, Zhang, Chunyan, Li, Jianjun, Sun, Keyuan, Zhang, Jindi, Huang, Mengyang, Wang, Jiaqiang
Publikováno v:
In Catalysis Communications February 2024 187
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