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Learning Contextualized Knowledge Structures for Commonsense Reasoning

Recently, neural-symbolic models have achieved noteworthy success in leveraging knowledge graphs (KGs) for commonsense reasoning tasks, like question answering (QA). However, fact sparsity, inherent in human-annotated KGs, can hinder such models from …

Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation

Knowledge graphs (KGs) have helped neural models improve performance on various knowledge-intensive tasks, like question answering and item recommendation. By using attention over the KG, such KG-augmented models can also "explain" which KG …

Egocentric Basketball Motion Planning from a Single First-Person Image

We present a model that uses a single first-person image to generate an egocentric basketball motion sequence in the form of a 12D camera configuration trajectory, which encodes a player's 3D location and 3D head orientation throughout the sequence. …

6-DoF Object Pose from Semantic Keypoints

This paper presents a novel approach to estimating the continuous six degree of freedom (6-DoF) pose (3D translation and rotation) of an object from a single RGB image. The approach combines semantic keypoints predicted by a convolutional network …

Scalable Vision System for Mouse Homecage Ethology

In recent years, researchers and laboratory support companies have recognized the utility of automated profiling of laboratory mouse activity and behavior in the home-cage. Video-based systems have emerged as a viable solution for non-invasive mouse …