Science

A new approach combats popularity bias in recommender systems, improving the relevance and variety of suggestions users receive.

A new approach allows teams of agents to coordinate effectively even when they have differing understandings of the world.

A new approach combines system identification with reinforcement learning to achieve efficient and accurate control of complex dynamics.

Researchers have developed a novel, tuning-free method that significantly improves the quality and coherence of images restored with text prompts.

New research reveals that removing demographic information from large language models to address bias isn’t a simple fix, and can actually reduce performance.

A new framework combines large language models and reinforcement learning to enable more robust and adaptable vision-language navigation in real-world settings.

A new method significantly accelerates the solution of large sparse linear systems on GPUs while minimizing memory usage.

Researchers are leveraging lane topology and symmetry to build a more efficient and scalable representation of traffic scenes, improving the accuracy of multi-agent trajectory forecasting.

New research sheds light on how distilled AI models learn, pinpointing the origins of their decision-making processes.

A new method leverages the speed of event cameras and optical flow to achieve robust and accurate 6DoF object pose tracking in dynamic environments.