Your question is Focal Loss vs Cross-Entropy. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are comparing training objectives for an object detection model and need to explain when one loss function is a better fit than another. The discussion is centered on how the loss changes model behavior, especially when easy negatives dominate training.
What are the trade-offs between different loss functions for object detection, such as Focal Loss versus standard Cross-Entropy?