Read the following scenario and provide your recommendation, justifying your reasoning.

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BERT models are built to represent either individual sentences or pairs of sentences, equipping them to tackle a variety of downstream language understanding problems. When a task requires handling two sentences simultaneously, the input is arranged as a single combined sequence containing both sentences, typically denoted as $$\mathrm{Sent}_{A}$$ and $$\mathrm{Sent}_{B}$$.

BERT Input Representation: Single and Paired Sentences

A simple method for designing a self-supervised classification task to train an encoder is Next Sentence Prediction (NSP), as presented in the original BERT paper. This approach is built on the assumption that a good text encoder should effectively capture the relationship between two sentences. To model this, NSP uses the output of encoding two consecutive sentences, $$\mathrm{Sent}_{A}$$ and $$\mathrm{Sent}_{B}$$, to determine whether $$\mathrm{Sent}_{B}$$ is indeed the next sentence following $$\mathrm{Sent}_{A}$$. For example, if $$\mathrm{Sent}_{A}$$ is 'It is raining .' and $$\mathrm{Sent}_{B}$$ is 'I need an umbrella .', the model is tasked with recognizing this sequential relationship.

Next Sentence Prediction (NSP)

A language representation model is designed with the flexibility to process either a single piece of text or a pair of texts as its input, allowing it to be adapted for a wide variety of tasks. Which of the following tasks would most directly benefit from the model's ability to process a pair of texts?

When handling sentence pairs, BERT processes them as a unified sequence. This sequence begins with a `[CLS]` token, followed by the first sentence (denoted as $$\mathrm{Sent}_{A}$$), a separator token `[SEP]`, the second sentence ($$\mathrm{Sent}_{B}$$), and a concluding `[SEP]` token. As established in the original BERT paper, the `[SEP]` token explicitly marks the boundary between the two sentences. This general input representation is formally expressed as the sequence: `[CLS] SentA [SEP] SentB [SEP]`.

BERT Input Format for Sentence Pairs

Consider two distinct language processing tasks: (1) Classifying the sentiment of a single movie review as positive or negative, and (2) Determining if a given question is a paraphrase of another question. For each task, state whether a single-text input or a paired-text input would be more appropriate for a model designed to handle both formats, and briefly justify your choice for each.

Choosing Input Formats for Language Tasks

A language model is being used for four different tasks. Three of these tasks are best addressed by providing the model with a pair of texts to analyze their relationship. One task, however, only requires a single text input. Which task is the outlier that would be handled using a single text input?

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