GNC-Pose achieves competitive 6D pose accuracy on the YCB dataset for textured objects using only geometric priors, rendering initialization, and robust GNC optimization without any learned features or training data.
Learning through Dialogue Interactions by Asking Questions
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Pith papers citing it
abstract
A good dialogue agent should have the ability to interact with users by both responding to questions and by asking questions, and importantly to learn from both types of interaction. In this work, we explore this direction by designing a simulator and a set of synthetic tasks in the movie domain that allow such interactions between a learner and a teacher. We investigate how a learner can benefit from asking questions in both offline and online reinforcement learning settings, and demonstrate that the learner improves when asking questions. Finally, real experiments with Mechanical Turk validate the approach. Our work represents a first step in developing such end-to-end learned interactive dialogue agents.
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UNVERDICTED 2representative citing papers
A rationale is presented for developing an assistant in Minecraft to advance natural language understanding and dialogue learning.
citing papers explorer
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GNC-Pose: Geometry-Aware GNC-PnP for Accurate 6D Pose Estimation
GNC-Pose achieves competitive 6D pose accuracy on the YCB dataset for textured objects using only geometric priors, rendering initialization, and robust GNC optimization without any learned features or training data.
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Why Build an Assistant in Minecraft?
A rationale is presented for developing an assistant in Minecraft to advance natural language understanding and dialogue learning.