We propose a shared task on training instance selection for few-shot neural text generation. Large-scale pretrained language models have led to dramatic improvements in few-shot text generation. Nonetheless, almost all previous work simply applies ra
ndom sampling to select the few-shot training instances. Little to no attention has been paid to the selection strategies and how they would affect model performance. Studying the selection strategy can help us (1) make the most use of our annotation budget in downstream tasks and (2) better benchmark few-shot text generative models. We welcome submissions that present their selection strategies and the effects on the generation quality.
Ploycystic ovary syndrome is one of the most common endocrine disorders in women, affecting 6-10% of reproductive-aged women.
The dermatological manifestations of hyperparathyroidism, hirsutism, acne vulgaris, androgenic alopecia and acanthosis nigricans are among the cardinal manifestations of PCOS
