Detailed Instructions: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
Problem:Below, we explore different ways to back off when the ScRNN predicts UNK (a frequent outcome for rare and unseen words):

Pass-through: word-recognizer passes on the (possibly misspelled) word as is.

Backoff to neutral word: Alternatively, noting that passing $\colorbox {gray!20}{\texttt {UNK}}$ -predicted words through unchanged exposes the downstream model to potentially corrupted text, we consider backing off to a neutral word like `a', which has a similar distribution across classes.

Backoff to background model: We also consider falling back upon a more generic word recognition model trained upon a larger, less-specialized corpus whenever the foreground word recognition model predicts UNK. Figure 1 depicts this scenario pictorially.
Solution:
How do the backoff strategies work?