6 citations · 6 across the 3 of their papers we have counts for
5 papers
Vision language models are unreliable at trivial spatial cognition
Sangeet Khemlani, Tyler Tran, Nathaniel Gyory +6
Vision language models (VLMs) are designed to extract relevant visuospatial information from images. Some research suggests that VLMs can exhibit humanlike scene understanding, whi…
"Can you do this?" Self-Assessment Dialogues with Autonomous Robots Before, During, and After a Mission
Tyler Frasca, Evan Krause, Ravenna Thielstrom +1
Autonomous robots with sophisticated capabilities can make it difficult for human instructors to assess its capabilities and proficiencies. Therefore, it is important future robots…
Engaging in Dialogue about an Agent's Norms and Behaviors
Daniel Kasenberg, Antonio Roque, Ravenna Thielstrom +1
We present a set of capabilities allowing an agent planning with moral and social norms represented in temporal logic to respond to queries about its norms and behaviors in natural…
Generating Justifications for Norm-Related Agent Decisions
Daniel Kasenberg, Antonio Roque, Ravenna Thielstrom +2
We present an approach to generating natural language justifications of decisions derived from norm-based reasoning. Assuming an agent which maximally satisfies a set of rules spec…
Augmenting Robot Knowledge Consultants with Distributed Short Term Memory
Tom Williams, Ravenna Thielstrom, Evan Krause +2
Human-robot communication in situated environments involves a complex interplay between knowledge representations across a wide variety of modalities. Crucially, linguistic informa…