24 citations · 77 across the 11 of their papers we have counts for
4 papers · 1 filter
KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA
Kenneth Marino, Xinlei Chen, Devi Parikh +2
One of the most challenging question types in VQA is when answering the question requires outside knowledge not present in the image. In this work we study open-domain knowledge, t…
Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Grasping
Adithyavairavan Murali, Weiyu Liu, Kenneth Marino +2
Despite the enormous progress and generalization in robotic grasping in recent years, existing methods have yet to scale and generalize task-oriented grasping to the same extent. T…
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
Valerie Chen, Abhinav Gupta, Kenneth Marino
Complex, multi-task problems have proven to be difficult to solve efficiently in a sparse-reward reinforcement learning setting. In order to be sample efficient, multi-task learnin…
Empirically Verifying Hypotheses Using Reinforcement Learning
Kenneth Marino, Rob Fergus, Arthur Szlam +1
This paper formulates hypothesis verification as an RL problem. Specifically, we aim to build an agent that, given a hypothesis about the dynamics of the world, can take actions to…