23 citations · 39 across the 4 of their papers we have counts for
4 papers
PROFIT: A Specialized Optimizer for Deep Fine Tuning
Anirudh S Chakravarthy, Shuai Kyle Zheng, Xin Huang +4
The fine-tuning of pre-trained models has become ubiquitous in generative AI, computer vision, and robotics. Although much attention has been paid to improving the efficiency of fi…
Language Understanding for Field and Service Robots in a Priori Unknown Environments
Matthew R. Walter, Siddharth Patki, Andrea F. Daniele +7
Contemporary approaches to perception, planning, estimation, and control have allowed robots to operate robustly as our remote surrogates in uncertain, unstructured environments. T…
Generalized Grounding Graphs: A Probabilistic Framework for Understanding Grounded Commands
Thomas Kollar, Stefanie Tellex, Matthew Walter +8
Many task domains require robots to interpret and act upon natural language commands which are given by people and which refer to the robot's physical surroundings. Such interpreta…
Learning Models for Following Natural Language Directions in Unknown Environments
Sachithra Hemachandra, Felix Duvallet, Thomas M. Howard +3
Natural language offers an intuitive and flexible means for humans to communicate with the robots that we will increasingly work alongside in our homes and workplaces. Recent advan…