What does "Task-Recency Bias" mean?
Table of Contents
Task-recency bias is a problem that occurs in learning systems, especially when these systems are trained on a series of tasks over time. When new tasks are introduced, the system may focus too much on the most recent tasks and not pay enough attention to older ones. This can lead to a drop in performance on tasks that were learned earlier.
Why It Matters
In many real-world applications, machines need to learn from new data while still remembering what they learned before. When task-recency bias kicks in, the machine can forget important information, making it less effective at performing its job.
How It Affects Learning
As new tasks come in, the system's ability to handle earlier tasks can suffer. This bias can be especially noticeable if the system's structure changes during training, which can cause the information about older tasks to become less accessible.
Solutions
Addressing task-recency bias involves methods that help the system maintain a balance between remembering past tasks and adapting to new ones. Strategies may include adjusting how the system processes different tasks and ensuring that it gives appropriate attention to all the tasks it has learned.