3 papers
cs.CV2021
How Transferable are Reasoning Patterns in VQA?
Corentin Kervadec, Theo Jaunet, Grigory Antipov +3
Since its inception, Visual Question Answering (VQA) is notoriously known as a task, where models are prone to exploit biases in datasets to find shortcuts instead of performing hi…
cs.CV2021
VisQA: X-raying Vision and Language Reasoning in Transformers
Theo Jaunet, Corentin Kervadec, Romain Vuillemot +3
Visual Question Answering systems target answering open-ended textual questions given input images. They are a testbed for learning high-level reasoning with a primary use in HCI,…
cs.LG2019
DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning
Theo Jaunet, Romain Vuillemot, Christian Wolf
We present DRLViz, a visual analytics interface to interpret the internal memory of an agent (e.g. a robot) trained using deep reinforcement learning. This memory is composed of la…