24 citations · 77 across the 11 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.LG2023★ 9 cited
Collaborating with language models for embodied reasoning
Ishita Dasgupta, Christine Kaeser-Chen, Kenneth Marino +4
Reasoning in a complex and ambiguous environment is a key goal for Reinforcement Learning (RL) agents. While some sophisticated RL agents can successfully solve difficult tasks, th…
cs.AI2023★ 3 cited
Distilling Internet-Scale Vision-Language Models into Embodied Agents
Theodore Sumers, Kenneth Marino, Arun Ahuja +2
Instruction-following agents must ground language into their observation and action spaces. Learning to ground language is challenging, typically requiring domain-specific engineer…