9 citations · 16 across the 6 of their papers we have counts for
6 papers
Think Before You Act: Unified Policy for Interleaving Language Reasoning with Actions
Lina Mezghani, Piotr Bojanowski, Karteek Alahari +1
The success of transformer models trained with a language modeling objective brings a promising opportunity to the reinforcement learning framework. Decision Transformer is a step…
Learning Goal-Conditioned Policies Offline with Self-Supervised Reward Shaping
Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski +2
Developing agents that can execute multiple skills by learning from pre-collected datasets is an important problem in robotics, where online interaction with the environment is ext…
Walk the Random Walk: Learning to Discover and Reach Goals Without Supervision
Lina Mezghani, Sainbayar Sukhbaatar, Piotr Bojanowski +1
Learning a diverse set of skills by interacting with an environment without any external supervision is an important challenge. In particular, obtaining a goal-conditioned agent th…
Memory-Augmented Reinforcement Learning for Image-Goal Navigation
Lina Mezghani, Sainbayar Sukhbaatar, Thibaut Lavril +4
In this work, we present a memory-augmented approach for image-goal navigation. Earlier attempts, including RL-based and SLAM-based approaches have either shown poor generalization…
Learning to Visually Navigate in Photorealistic Environments Without any Supervision
Lina Mezghani, Sainbayar Sukhbaatar, Arthur Szlam +2
Learning to navigate in a realistic setting where an agent must rely solely on visual inputs is a challenging task, in part because the lack of position information makes it diffic…
Understanding Image Quality and Trust in Peer-to-Peer Marketplaces
Xiao Ma, Lina Mezghani, Kimberly Wilber +4
As any savvy online shopper knows, second-hand peer-to-peer marketplaces are filled with images of mixed quality. How does image quality impact marketplace outcomes, and can qualit…