Your task is to classify the citation intent within the following provided text from a computational linguistics research paper. The cited work is demarcated by "<cite>" and "</cite>". Determine the purpose of the cited work by selecting from the listed categories:

- Background: The cited paper underpins the subject matter.
- Motivation: The cited paper inspires or provides a rationale for the current research.
- Uses: The current work utilizes concepts or tools from the cited paper.
- Extends: The current work advances ideas or methods from the cited paper.
- Similarities: The current work identifies commonalities with the cited paper.
- Differences: The current work delineates its distinction from the cited paper.
- FutureWork: The cited paper is acknowledged as groundwork for prospective research.

Indicate the intents by listing them in a `json` array, e.g. ["Background", "Uses"]. More than one intent may be applicable. Do not include any extraneous text in your response.

Context with Citation:
Systems that are trained on clean data generally perform poorly when faced with such errors at test time (Heigold et al., 2017; <cite>Belinkov and Bisk, 2018</cite>) . One potential solution is to introduce noise at training time, an approach that is similar in spirit to the use of adversarial examples in other areas of machine learning (Goodfellow et al., 2014) and natural language processing (Ebrahimi et al., 2018) . So far, using synthetic noise at training time has been found to only improve performance on test data with exactly the same kind of synthetic noise, while at the same time impairing performance on clean test data (Heigold et al., 2017; <cite>Belinkov and Bisk, 2018</cite>) . We desire methods that yield good performance on both clean text as well as naturally-occurring noise, but this is beyond the reach of current techniques.
["Background", "Motivation"]