High Recall

High recall, the ability of a system to retrieve all relevant information, is a crucial objective across diverse fields, from natural language processing to visual place recognition. Current research focuses on improving recall in various models, including recurrent neural networks and transformers, often addressing limitations in memory capacity and information selection strategies. This pursuit is driven by the need for more robust and complete information retrieval in applications ranging from improved dialogue systems and more accurate object detection to efficient resource utilization in embedded systems. The development of novel evaluation metrics and algorithms to mitigate issues like duplicate predictions and improve the precision-recall trade-off is also a significant area of ongoing investigation.