In the recent shift towards human-centric AI, the need for machines to accurately use natural
language has become increasingly important. While a common approach to achieve this is …

Neural captioners are typically trained to mimic human-generated references without
optimizing for any specific communication goal, leading to problems such as the generation …

We propose a simple yet effective and robust method for contrastive captioning: generating
discriminative captions that distinguish target images from very similar alternative distractor …

As large pre-trained image-processing neural networks are being embedded in autonomous
agents such as self-driving cars or robots, the question arises of how such systems can …

Multi-Agent Reinforcement Learning (MARL) methods have shown promise in enabling
agents to learn a shared communication protocol from scratch and accomplish challenging …

Abstract Machine learning has proven extremely useful in many applications in recent years.
However, a lot of these success stories stem from evaluating the algorithms on data very …

Multi-Agent Reinforcement Learning (MARL) methods have shown promise in enabling
agents to learn a shared communication protocol from scratch and accomplish challenging …