2 citations · 2 across the 6 of their papers we have counts for
6 papers
Understanding Common Ground Misalignment in Goal-Oriented Dialog: A Case-Study with Ubuntu Chat Logs
Rupak Sarkar, Neha Srikanth, Taylor Hudson +3
While it is commonly accepted that maintaining common ground plays a role in conversational success, little prior research exists connecting conversational grounding to success in…
FRIDA to the Rescue! Analyzing Synthetic Data Effectiveness in Object-Based Common Sense Reasoning for Disaster Response
Mollie Shichman, Claire Bonial, Austin Blodgett +3
During Human Robot Interactions in disaster relief scenarios, Large Language Models (LLMs) have the potential for substantial physical reasoning to assist in mission objectives. Ho…
Beyond Memorization: Assessing Semantic Generalization in Large Language Models Using Phrasal Constructions
Wesley Scivetti, Melissa Torgbi, Austin Blodgett +4
The web-scale of pretraining data has created an important evaluation challenge: to disentangle linguistic competence on cases well-represented in pretraining data from generalizat…
SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus
Stephanie M. Lukin, Claire Bonial, Matthew Marge +14
We introduce the Situated Corpus Of Understanding Transactions (SCOUT), a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration. The corpus…
Human-Robot Dialogue Annotation for Multi-Modal Common Ground
Claire Bonial, Stephanie M. Lukin, Mitchell Abrams +11
In this paper, we describe the development of symbolic representations annotated on human-robot dialogue data to make dimensions of meaning accessible to autonomous systems partici…
Navigating to Success in Multi-Modal Human-Robot Collaboration: Analysis and Corpus Release
Stephanie M. Lukin, Kimberly A. Pollard, Claire Bonial +4
Human-guided robotic exploration is a useful approach to gathering information at remote locations, especially those that might be too risky, inhospitable, or inaccessible for huma…