57 citations · 105 across the 13 of their papers we have counts for
20 papers
Attention in Reasoning: Dataset, Analysis, and Modeling
Shi Chen, Ming Jiang, Jinhui Yang +1
While attention has been an increasingly popular component in deep neural networks to both interpret and boost the performance of models, little work has examined how attention pro…
REX: Reasoning-aware and Grounded Explanation
Shi Chen, Qi Zhao
Effectiveness and interpretability are two essential properties for trustworthy AI systems. Most recent studies in visual reasoning are dedicated to improving the accuracy of predi…
Learning to Predict Trustworthiness with Steep Slope Loss
Yan Luo, Yongkang Wong, Mohan S. Kankanhalli +1
Understanding the trustworthiness of a prediction yielded by a classifier is critical for the safe and effective use of AI models. Prior efforts have been proven to be reliable on…
AiR: Attention with Reasoning Capability
Shi Chen, Ming Jiang, Jinhui Yang +1
While attention has been an increasingly popular component in deep neural networks to both interpret and boost performance of models, little work has examined how attention progres…
Saliency Prediction with External Knowledge
Yifeng Zhang, Ming Jiang, Qi Zhao
The last decades have seen great progress in saliency prediction, with the success of deep neural networks that are able to encode high-level semantics. Yet, while humans have the…
-Reference Transfer Learning for Saliency Prediction
Yan Luo, Yongkang Wong, Mohan S. Kankanhalli +1
Benefiting from deep learning research and large-scale datasets, saliency prediction has achieved significant success in the past decade. However, it still remains challenging to p…