13 citations · 40 across the 5 of their papers we have counts for
5 papers
Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding
Qingxing Cao, Bailin Li, Xiaodan Liang +2
Though beneficial for encouraging the Visual Question Answering (VQA) models to discover the underlying knowledge by exploiting the input-output correlation beyond image and text c…
EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning
Bailin Li, Bowen Wu, Jiang Su +2
Finding out the computational redundant part of a trained Deep Neural Network (DNN) is the key question that pruning algorithms target on. Many algorithms try to predict model perf…
Explainable High-order Visual Question Reasoning: A New Benchmark and Knowledge-routed Network
Qingxing Cao, Bailin Li, Xiaodan Liang +1
Explanation and high-order reasoning capabilities are crucial for real-world visual question answering with diverse levels of inference complexity (e.g., what is the dog that is ne…
Interpretable Visual Question Answering by Reasoning on Dependency Trees
Qingxing Cao, Bailin Li, Xiaodan Liang +1
Collaborative reasoning for understanding image-question pairs is a very critical but underexplored topic in interpretable visual question answering systems. Although very recent s…
Visual Question Reasoning on General Dependency Tree
Qingxing Cao, Xiaodan Liang, Bailing Li +2
The collaborative reasoning for understanding each image-question pair is very critical but under-explored for an interpretable Visual Question Answering (VQA) system. Although ver…