44 citations · 91 across the 3 of their papers we have counts for
7 papers
Sim2Real Predictivity: Does Evaluation in Simulation Predict Real-World Performance?
Abhishek Kadian, Joanne Truong, Aaron Gokaslan +6
Does progress in simulation translate to progress on robots? If one method outperforms another in simulation, how likely is that trend to hold in reality on a robot? We examine thi…
12-in-1: Multi-Task Vision and Language Representation Learning
Jiasen Lu, Vedanuj Goswami, Marcus Rohrbach +2
Much of vision-and-language research focuses on a small but diverse set of independent tasks and supporting datasets often studied in isolation; however, the visually-grounded lang…
Question-Conditioned Counterfactual Image Generation for VQA
Jingjing Pan, Yash Goyal, Stefan Lee
While Visual Question Answering (VQA) models continue to push the state-of-the-art forward, they largely remain black-boxes - failing to provide insight into how or why an answer i…
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
Erik Wijmans, Abhishek Kadian, Ari Morcos +5
We present Decentralized Distributed Proximal Policy Optimization (DD-PPO), a method for distributed reinforcement learning in resource-intensive simulated environments. DD-PPO is…
Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation
Arijit Ray, Karan Sikka, Ajay Divakaran +2
While models for Visual Question Answering (VQA) have steadily improved over the years, interacting with one quickly reveals that these models lack consistency. For instance, if a…
Emergence of Compositional Language with Deep Generational Transmission
Michael Cogswell, Jiasen Lu, Stefan Lee +2
Recent work has studied the emergence of language among deep reinforcement learning agents that must collaborate to solve a task. Of particular interest are the factors that cause…