11 citations · 13 across the 6 of their papers we have counts for
6 papers
Episodic memory in AI agents poses risks that should be studied and mitigated
Chad DeChant
Most current AI models have little ability to store and later retrieve a record or representation of what they do. In human cognition, episodic memories play an important role in b…
Episodic Memory Verbalization using Hierarchical Representations of Life-Long Robot Experience
Leonard Bärmann, Chad DeChant, Joana Plewnia +4
Verbalization of robot experience, i.e., summarization of and question answering about a robot's past, is a crucial ability for improving human-robot interaction. Previous works ap…
Learning to Summarize and Answer Questions about a Virtual Robot's Past Actions
Chad DeChant, Iretiayo Akinola, Daniel Bauer
When robots perform long action sequences, users will want to easily and reliably find out what they have done. We therefore demonstrate the task of learning to summarize and answe…
Summarizing a virtual robot's past actions in natural language
Chad DeChant, Daniel Bauer
We propose and demonstrate the task of giving natural language summaries of the actions of a robotic agent in a virtual environment. We explain why such a task is important, what m…
Automated Weed Detection in Aerial Imagery with Context
Delia Bullock, Andrew Mangeni, Tyr Wiesner-Hanks +7
In this paper, we demonstrate the ability to discriminate between cultivated maize plant and grass or grass-like weed image segments using the context surrounding the image segment…
Shape Completion Enabled Robotic Grasping
Jacob Varley, Chad DeChant, Adam Richardson +2
This work provides an architecture to enable robotic grasp planning via shape completion. Shape completion is accomplished through the use of a 3D convolutional neural network (CNN…