1 citations · 1 across the 5 of their papers we have counts for
5 papers
Hierarchical Compositionality for An Assistive AI Agent
Tianyi Fu, Mohan Sridharan
AI agents are increasingly being developed to assist humans in various applications, and Large Language Models and other deep network architectures are considered to be state of th…
Anticipate, Adapt, Act: A Hybrid Framework for Task Planning
Nabanita Dash, Ayush Kaura, Shivam Singh +4
Anticipating and adapting to failures is a key capability robots need to collaborate effectively with humans in complex domains. This continues to be a challenge despite the impres…
AdaptBot: Combining LLM with Knowledge Graphs and Human Input for Generic-to-Specific Task Decomposition and Knowledge Refinement
Shivam Singh, Karthik Swaminathan, Nabanita Dash +4
An embodied agent assisting humans is often asked to complete new tasks, and there may not be sufficient time or labeled examples to train the agent to perform these new tasks. Lar…
Anticipate & Act : Integrating LLMs and Classical Planning for Efficient Task Execution in Household Environments
Raghav Arora, Shivam Singh, Karthik Swaminathan +6
Assistive agents performing household tasks such as making the bed or cooking breakfast often compute and execute actions that accomplish one task at a time. However, efficiency ca…
Anticipate & Collab: Data-driven Task Anticipation and Knowledge-driven Planning for Human-robot Collaboration
Shivam Singh, Karthik Swaminathan, Raghav Arora +6
An agent assisting humans in daily living activities can collaborate more effectively by anticipating upcoming tasks. Data-driven methods represent the state of the art in task ant…