Mode collapse is problematic because... It requires more data It makes the discriminator weak
Answer options
A
None of the given options
B
It limits the diversity of generated outputs
C
It speeds up training
Correct answer: It limits the diversity of generated outputs
Explanation
Mode collapse in GANs is problematic because the generator produces only a limited subset of possible outputs — it collapses to generating similar/identical samples regardless of the input noise — severely limiting the diversity of generated outputs and failing to capture the full data distribution.